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Accelerate agentic planning with trusted data productsAccelerate agentic planning with trusted data productsGoverned data products as the ground for AI planning in SAP Analytics Cloud: using a ready data product or building one in SAP Business Data Cloud, the cataloguing and lineage concern, then agentic AI automating planning tasks and producing insights on top. The abstract names the two products and the data product step and does not say which planning tasks the agents take over. A TechEd 2026 hands-on session (Thursday 29 October, Berlin), presented by Jie Deng, Maximilian Paul Gander and Richard Mooney, written here from SAP's abstract; the recording is not yet published.
Explore your Hyperscaler data with SAP Business Data CloudExplore your Hyperscaler data with SAP Business Data CloudSAP's map of the ways data held on hyperscaler and partner platforms is joined with SAP data in SAP Business Data Cloud, with a sub-page each for AWS, Azure, Google Cloud, Databricks and Snowflake. It sets four modes side by side: BDC Connect shares data products in both directions over the Delta Sharing protocol from the object store layer, while in the SAP Datasphere layer federation reads remote tables in place, Replication Flows copy SAP data out to stores such as Amazon S3 or Google BigQuery, and Data Flows import files and transform them into Datasphere tables, the last three being the ground loading a warehouse covers. The Snowflake and BigQuery connectors are dated to 2026 releases, and a closing page lists what slows federation, from source and tenant in different regions to queries that do not filter and aggregate at the source.published 2026-05-08
Federated Machine Learning with SAP DatasphereFederated Machine Learning with SAP DatasphereSAP's design for training predictive models on an external machine learning platform against SAP Datasphere data that is not replicated to that platform. The open-source FedML Python library runs in the platform's notebook, connects to Datasphere over Python/SQLDBC and reads the analytic models in which Datasphere unifies SAP and non-SAP sources; a trained model can then be deployed to SAP AI Core, or in several sub-pages to SAP BTP, Kyma runtime, which is the predictive models path where training happens outside SAP. Sub-pages cover Amazon SageMaker, Azure Machine Learning, Google Vertex AI, Databricks, NVIDIA RAPIDS on GPUs and IBM watsonx.published 2025-01-23
Flexible analytics at speed: Calculation views in SAP Business Data CloudFlexible analytics at speed: Calculation views in SAP Business Data CloudCalculation views in SAP HANA Cloud, the reusable analytic modelling blocks built in its graphical modelling environment, with three newer parts the abstract names: AI-assisted modelling, refactoring, and advanced materialisation, and the way the views sit inside SAP Business Data Cloud. What a materialisation is chosen on, and what the AI assistance generates, is not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hansika Colomboge Dona, Jan Zwickel, Niklas Siemer and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
SAP Datasphere Integration Patterns: Lessons Learned from Two Years of ImplementationsSAP Datasphere Integration Patterns: Lessons Learned from Two Years of ImplementationsTwo years of production SAP Datasphere integrations across SAP and non-SAP sources, settling on Replication Flows over remote access for high-volume Finance analytics because remote queries added latency at query time, then tuning the copy with Datasphere-side partitioning, source-side CDS view optimisation and Cloud Connector sizing. For file-based and Kafka sources, SAP Integration Suite iFlows did work a direct connection could not — flattening nested JSON, PGP decryption and orchestrating the SAP Ariba extraction built on SAP's own BTP Procurement Data Extractor content.saikrishna_kalivarapu2, published 2026-08-17
Strategy and Tool Updates on BW Modernization with SAP Business Data CloudStrategy and Tool Updates on BW Modernization with SAP Business Data CloudDevtoberfest 2026 session DAT-13, in which a product manager for SAP Business Data Cloud sets out the revised BW modernisation strategy, now called optimise, modernise and innovate, and the three tools that carry it. The data product generator transfers BW InfoProviders into local table files in a dedicated BW inbound space of SAP Datasphere, where a data product is still created by hand in the data sharing cockpit; the query template generator turns BW query metadata into an analytical model template in the HANA space; the BW migration assistant, planned to start in Q4 for BW NetWeaver, takes the data flows and transformations below them, and is shown on slides only. That is the loading a warehouse edge, and the demos cover the BW/4HANA cockpit, the ABAP program for the NetWeaver GUI, mass generation with semantics from the BW modeling tools, and the flattening operator for sharing data outside SAP.SAP Developers, published 2026-09-22
Transform business data into AI-supported insightsTransform business data into AI-supported insightsBusiness metrics turned into insights, narratives and recommendations by SAP Joule's agents, with People Intelligence, the SAP Snowflake solution extension for SAP Business Data Cloud and SAP Analytics Cloud connected in SAP Business Data Cloud. The abstract names what is connected and what comes out, and does not say what the exercise builds or where the Snowflake extension sits in it; People Intelligence and the extension are not atlas entries. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Babacar Toure, Maximilian Paul Gander, Neetha Pucknat and San Tran, written here from SAP's abstract; the recording is not yet published.
Updates on Embedded Analytics in ABAP Cloud for DevelopersUpdates on Embedded Analytics in ABAP Cloud for DevelopersA Devtoberfest 2026 session (ABA-33) on the generator wizards for Embedded Analytics in ABAP Cloud, run by right-clicking a data definition in the ADT Project Explorer. It first names the artefacts a star schema needs, all of them ABAP CDS — cube view at its centre, dimension, text and hierarchy views reached by association, a hierarchy directory, and an InA service definition and binding — and then generates them: the star schema generator reads a view entity's metadata, sorts its fields into dimensions and measures, asks about the ones it cannot decide, offers the dimension views it found and writes an activated cube view; the hierarchy generator produces directory, node, base and definition views plus a maintenance business object with a generated app, which is used to group airlines into alliances before the hierarchy is switched on in the layout of the multi-dimensional analysis app. That is analytic modelling on the ABAP platform, which is what the edges rest on; the outlook names time-dependent hierarchies, translatable texts and dimensions generated from database tables.published 2026-10-05
A method to create an Adobe form attachment for a work item using the class concept.A method to create an Adobe form attachment for a work item using the class concept.Walks through an ABAP workflow class, ZCL_WF_PDF, whose methods call an Adobe form through a Form-Builder-generated function module, convert the returned PDF between hexadecimal string and binary with SCMS_XSTRING_TO_BINARY and SCMS_BINARY_TO_XSTRING, and attach it to a work item via SAP_WAPI_ATTACHMENT_ADD and SAP_WAPI_WRITE_CONTAINER, with the class, background-task and SWDD workflow steps shown in full. It explains document output's ABAP route, rendering a PDF through the Form Builder and getting it back into the program, and a route into attachments's ABAP side distinct from Generic Object Services: a file attached to an SAP Business Workflow work item instead.Mithun_Sharma1, published 2026-08-21
Building an Attachment Upload and Download Solution Using UploadSetwithTable ControlBuilding an Attachment Upload and Download Solution Using UploadSetwithTable ControlThe successor control to UploadSet posts the file in one request by default, and against CAP that is wrong: the record has to be created first and the content put to it afterwards. The author states the two-step shape plainly and notes it may not apply to an ABAP backend, which is the kind of boundary that usually goes unsaid. Written during a proof of concept for a reusable attachment component, and it carries the problem they hit with the control.published 2025-03-13
CAP Foundry: Engineering SAP CAP Applications from Business Intent with Guardrailed AICAP Foundry: Engineering SAP CAP Applications from Business Intent with Guardrailed AICAP Foundry is a prototype that generates a CAP Node.js project with SAP Fiori elements from a written business requirement, discovering the actual data shape from a chosen source — SQLite, a configured SAP HANA HDI container, offline EDMX, live OData through the SAP Destination service, or approved SAP BTP ABAP objects — instead of inventing one. The generated application can carry a Fiori draft lifecycle with optimistic concurrency via ETags and annotation-driven Fiori elements list and object screens, localized independently of the underlying service contract. Attachments can be added with upload, download and delete, gated on a malware-scan status, and the generated project still has to compile, build and pass its generated tests before the run is accepted.Shahid, published 2026-08-20
Configure Journal Entry Posting Approval from Store Template in Build Process AutomationConfigure Journal Entry Posting Approval from Store Template in Build Process AutomationWalks through deploying SAP's Journal Entry Posting Approval template from the SAP Build Process Automation Store against an on-premise S/4HANA system that has no Secure Network Connection: destinations for S/4HANA via Cloud Connector, for SAP Document Management service, integration option to hold the approval's supporting documents, and for the BPA service and its SMTP mail. It then swaps the template's SNC action groups for basic-connection BAPI calls and deploys the approval's UI5 applications so the task lands in My Inbox, with a Desktop Agent registered to run the unattended document-check and document-post automations.published 2025-01-28
Major updates to the Attachments plugin – multi-cloud support, malware scanning and moreMajor updates to the Attachments plugin – multi-cloud support, malware scanning and moreMulti-cloud storage and malware scanning added to the official plugin, framed through CAP's Calesi pattern — the argument being that a service interface is what lets the storage underneath change without the application noticing. The post that a triage bug hid: "attachment" had stopped matching "Attachments".published 2025-12-02
Major updates to the Attachments plugin – multi-cloud support, malware scanning and more
@cap-js/attachments 3.4.0, now 4.0.0, com.sap.cds:cds-feature-attachments 1.2.2. Affects A recipe, Runnable code.
Media Handling in SAP CAPM – Backend and Frontend ImplementationMedia Handling in SAP CAPM – Backend and Frontend ImplementationFiles against a record with the front end included, which most of the attachments writing here leaves out — the entity that stores the content, the custom logic around it, and then the UI5 side that uploads and retrieves. End to end rather than one half.published 2026-03-02
RAP - Native File UploadRAP - Native File UploadA workaround for uploading a file into a RAP application ahead of SAP's own upload and download solution, which is still pending: two abstract root entities — one holding the file's bytes, MIME type and filename, one for a popup dialog — joined by an association flagged with hierarchy, exposed through a static action declared with DEEP PARAMETER so the nested structure reaches the handler. The trade-offs are stated plainly: the popup takes no default values, only one file uploads at a time, and the UI annotation on the attachment field is ignored because its label is read from the sub-entity's own name.Björn S., published 2026-08-18
Uploading attachment with cap-js/attachment plugins but via External App/PostmanUploading attachment with cap-js/attachment plugins but via External App/PostmanThe plugin is written for a Fiori elements front end; this is the case where the caller is neither — Postman and a React app. Short, and it exists because the request shape is not obvious from outside the generated UI: what to POST, what to PUT, and in which order.published 2025-07-24
Use SAP Document Management Service Plugin In CAP NODEJS Step by Step GuidanceUse SAP Document Management Service Plugin In CAP NODEJS Step by Step GuidanceThe official plugin is documented in capire; this is somebody who set it up anyway and wrote down where it went wrong. The author says as much — the point is to spare customers the troubles, so the value is in the order of the steps and the prerequisites, not in the API.Jacky_Liu1, published 2025-03-06
Boosting performance in SAP Cloud Application Programming Model (CAP) applications with cds-cachingBoosting performance in SAP Cloud Application Programming Model (CAP) applications with cds-cachingThe plugin's introduction post: what cds-caching is for, how it is put together and the cases it was written against. The edge holds because the plugin's README still points here as the piece to read first, so this is where a reader arriving at the plugin is sent. It predates version 1.0 and the API has moved since: the read-through calls it shows as cache.run() and cache.send() are the ones the README now lists as deprecated in favour of cache.rt.*, which returns the cache key and hit/miss metadata alongside the result, and 1.0 made user, tenant and locale awareness opt-in under keyManagement rather than folding them into request-based keys by default. Metrics and monitoring, the OData API and full TypeScript definitions arrived with 1.0 and are described in CAP just got faster: What's new in cds-caching 1.0 instead. The reasoning about when a CAP service wants a cache still reads true; the call sites need translating.published 2025-06-25
Boosting performance in SAP Cloud Application Programming Model (CAP) applications with cds-caching
cds 9, maintenance until 2027-06, cds-caching 0.x, now 3.1.1. Affects A recipe.
CAP just got faster: What's new in cds-caching 1.0CAP just got faster: What's new in cds-caching 1.0What changed in cds-caching at 1.0, announced at reCAP 2025 by the plugin's own maintainer. The substantive change is the read-through API: cache.rt.run(), send(), exec() and wrap() replace the bare cache.run() and cache.send(), and each returns the cache key and hit-or-miss metadata beside the result rather than the value alone. The second is quieter and easier to miss on an upgrade: user, tenant and locale stopped being folded into request-based cache keys by default and became opt-in through keyManagement, or per operation through a key template. Both of those still describe 3.x. What does not is the second half of the post: the metrics configuration it shows was reshaped at 2.0 and the statistics and dashboard settings were removed at 3.0, so take the monitoring and dashboard sections from the README instead. Read it as the successor to the introduction post, which still shows the deprecated calls.published 2025-07-15
CAP just got faster: What's new in cds-caching 1.0
cds-caching 1.0, now 3.1.1, cds 9, maintenance until 2027-06. Affects A reference.
Performance Boost and Caching Strategy for Faster Data Access using "cds-caching" in SAP CAPPerformance Boost and Caching Strategy for Faster Data Access using "cds-caching" in SAP CAPSomebody else's account of using the plugin, which is the useful counterpart to its documentation. The case is specific: a master-data entity of more than a million rows, rarely written and constantly read, where the read-heavy shape is what makes caching worth the complexity rather than a general performance wish. Walks through integrating cds-caching into that application and what it changed.NaveenChandar, published 2025-03-04
Performance Boost and Caching Strategy for Faster Data Access using "cds-caching" in SAP CAP
cds-caching has been through 4 major lines since this was published, most recently 1 (2025-07), 2 (2026-07), 3 (2026-08). Affects A recipe, Runnable code.
🔴 Your Agent Wants to Call SAP. Now What?🔴 Your Agent Wants to Call SAP. Now What?Devtoberfest 2026 session INT-23, on what belongs between an agent and an SAP system. A solution advisor and an enterprise architect point Joule Desktop extensions at MCP servers built on API Management inside SAP Integration Suite, and ask it for business partners, orders and line items from an S/4HANA demo system; asked for the ten largest customers it answers from a sample of 200 orders rather than reading the whole table. They then open the API proxy behind it, where a spike arrest policy caps the backend at ten calls per second and the MCP server is configured to expose only the GET resources of the business-partner API so that an agent cannot create one, which is where the edges to Serve your application over MCP and Rate limiting hold. For totals across all sales orders they send the agent to SAP Business Data Cloud instead of the transactional system, since it aggregates and is read-only, and back through Integration Suite for writes such as journal entries.SAP Developers, published 2026-09-30
Accelerate agentic planning with trusted data productsAccelerate agentic planning with trusted data productsGoverned data products as the ground for AI planning in SAP Analytics Cloud: using a ready data product or building one in SAP Business Data Cloud, the cataloguing and lineage concern, then agentic AI automating planning tasks and producing insights on top. The abstract names the two products and the data product step and does not say which planning tasks the agents take over. A TechEd 2026 hands-on session (Thursday 29 October, Berlin), presented by Jie Deng, Maximilian Paul Gander and Richard Mooney, written here from SAP's abstract; the recording is not yet published.
Agent-to-agent in action: SAP and Adobe CX Enterprise Coworker at HenkelAgent-to-agent in action: SAP and Adobe CX Enterprise Coworker at HenkelA customer story: SAP's data agents and SAP Business Data Cloud with Adobe CX Enterprise Coworker putting enterprise data in front of Henkel's marketing teams, with faster decisions as the stated result. The abstract names Business Data Cloud as the data side of an agent-to-agent setup and says nothing about what it does there or how the two agents talk; neither Adobe's product nor the data agents are atlas entries. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Ankur Jain, Ramalingam Ramani and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Agentic SAP BW modernization: Your path to SAP Business Data CloudAgentic SAP BW modernization: Your path to SAP Business Data CloudStrategies for moving from SAP Business Warehouse to SAP Business Data Cloud, with dedicated migration tools and AI agents to shorten the move while keeping what was built in SAP BW, the platform migration concern for a warehouse. A Fresenius speaker co-presents; the abstract names neither the migration tools nor the agents. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Constantin Herbst, Hannes Keil and Sandy Tran, written here from SAP's abstract; the recording is not yet published.
AI-enhanced analytics with SAP Business AI PlatformAI-enhanced analytics with SAP Business AI PlatformSAP Business Data Cloud data products joined to an ontology, a semantic layer the abstract says is supported by the Model Context Protocol, and read from Joule Work (SAP Joule) and SAP Analytics Cloud: that is the architecture SAP's abstract states for its AI-enabled analytics. The abstract names the parts and not how the semantic layer is modelled or what an analytics developer builds against. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Hacen Benkhedah, Joaquin Recio Huertas, Matilda Hyka and Oliver Huth, written here from SAP's abstract; the recording is not yet published.
Architecting your data foundation for the Autonomous EnterpriseArchitecting your data foundation for the Autonomous EnterpriseBuilding a data foundation for what SAP calls the Autonomous Enterprise on SAP Business Data Cloud: a business data fabric that unifies trusted data, business context and governed data products across an organisation's systems, so that Joule Agents in SAP Joule have the context their answers rest on. The abstract states Business Data Cloud's role and no product, data product or integration beneath it. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Mudit Mittal and Prakash Nanduri, written here from SAP's abstract; the recording is not yet published.
Build agentic SAP extensions with Google CloudBuild agentic SAP extensions with Google CloudGoogle Cloud's architectures for agentic AI apps on SAP with a clean core: SAP Business AI Platform, SAP S/4HANA and SAP Business Data Cloud joined with BigQuery, Gemini and Google's Agent Development Kit. The abstract names zero-copy data agents, developer API workflows and ABAP extensions for AI integration, the last of which is the Extensibility concern; Business Data Cloud is the one atlas entry it names, and how any piece connects to another is not stated. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Ekaterina Kruse, Ian Moria and Stany Winkler, written here from SAP's abstract; the recording is not yet published.
Build AI agents on SAP and non-SAP data and context in an open lakehouseBuild AI agents on SAP and non-SAP data and context in an open lakehouseSAP Business Data Cloud as an open lakehouse: the abstract states that it holds third-party data beside SAP data and its semantic context on Apache Iceberg and Apache Polaris, that architects and developers publish governed data products and ontologies from it, which is the cataloguing and lineage concern, and that agents built on them for SAP Joule can be reached from outside over A2A. How a data product is defined, and what the ontology layer adds to it, is not in the abstract. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Rahim Bhojani and Sivakumar N, written here from SAP's abstract; the recording is not yet published.
Build and govern data products in the Joule Studio solutionBuild and govern data products in the Joule Studio solutionData products in SAP Business Data Cloud are built and deployed from Joule Studio, in SAP's abstract, with no-code, AI-assisted tools that combine SAP and third-party data, and are then governed, catalogued and shared for analytics and AI, the cataloguing and lineage concern on the product side. The abstract names the steps and not what a data product built this way contains or how Joule Studio reaches the data. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Arne Ludwig, Aruna Kashinath, Rene Kirchhoff and Sandy Tran, written here from SAP's abstract; the recording is not yet published.
Build real-time, unified data products for agentic AI with SAP ReltioBuild real-time, unified data products for agentic AI with SAP ReltioSAP Reltio inside SAP Business Data Cloud unifies master data across SAP and third-party systems and complements SAP Master Data Governance, in SAP's abstract, with Customer 360 as the named scenario and real-time data products for applications, analytics and AI as the output. The abstract states Reltio's place in the product and nothing about how the unification or the data products work. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Arne Ludwig, Rene Kirchhoff, Richard Mooney and Sriraj Rajaram, written here from SAP's abstract; the recording is not yet published.
Building custom Joule Agents with SAP Knowledge GraphBuilding custom Joule Agents with SAP Knowledge GraphCustom Joule Agents built in a hands-on with SAP Knowledge Graph and Joule Studio: discovering APIs from a user's intent, grounding an agent's answers in business context, and integrating data products for SAP Business Data Cloud. The agents are SAP Joule's; the Knowledge Graph is not an atlas entry, and the abstract does not say which Joule Studio edition the exercises use. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Jan Portisch, Lucas Kiesow, Pavithra G K and Rafael Martin, written here from SAP's abstract; no recording is announced.
Data Product Governance in SAP Business Data CloudData Product Governance in SAP Business Data CloudA Devtoberfest 2026 data-track session (DAT-41) on data product governance in SAP Business Data Cloud, released as an MVP: every data product belongs to a domain, a consumer puts one in a cart and raises an access request with a purpose, a target location and acknowledged terms and conditions, and a data steward's approval becomes an access agreement recording who uses which data product where. The demo runs both sides in the BDC cockpit — domains, access management and data product management for the steward, catalog, cart and request for the consumer, with Databricks as the target workspace — and that is what the Cataloguing and lineage edge rests on. It also states the current limits: one default domain until custom domains and subdomains arrive, auto-approved requests for space copies, transports and intelligent content, stewards who cannot yet revoke an active agreement, and an install step still done by hand after approval.SAP Developers
Enhancing agentic AI with trusted business dataEnhancing agentic AI with trusted business dataHow SAP Business Data Cloud gives AI applications and agents governed access to business data and its context, and how zero-copy architectures let AI read enterprise data with less of it moved, which is the data federation concern. The abstract names the product and the architecture and states no mechanism or product the zero-copy path runs over. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA100V, virtual), presented by Aruna Kashinath, Hannes Keil and San Tran, written here from SAP's abstract; the recording is not yet published.
Enriching AI models with SAP AI Core in SAP Business Data CloudEnriching AI models with SAP AI Core in SAP Business Data CloudThe integration between SAP Business Data Cloud and SAP AI Core, through which data products with their semantics feed AI models for benchmarking, custom AI development and agentic analytics and applications. The abstract names the two products and the three uses and states nothing about how the data reaches AI Core or what the integration consists of. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by San Tran and Sandy Tran, written here from SAP's abstract; the recording is not yet published.
Explore your Hyperscaler data with SAP Business Data CloudExplore your Hyperscaler data with SAP Business Data CloudSAP's map of the ways data held on hyperscaler and partner platforms is joined with SAP data in SAP Business Data Cloud, with a sub-page each for AWS, Azure, Google Cloud, Databricks and Snowflake. It sets four modes side by side: BDC Connect shares data products in both directions over the Delta Sharing protocol from the object store layer, while in the SAP Datasphere layer federation reads remote tables in place, Replication Flows copy SAP data out to stores such as Amazon S3 or Google BigQuery, and Data Flows import files and transform them into Datasphere tables, the last three being the ground loading a warehouse covers. The Snowflake and BigQuery connectors are dated to 2026 releases, and a closing page lists what slows federation, from source and tenant in different regions to queries that do not filter and aggregate at the source.published 2026-05-08
Joule and SAP Knowledge Graph: Context-aware AI across SAP solutionsJoule and SAP Knowledge Graph: Context-aware AI across SAP solutionsThe catalogue carries RA107's abstract under this title, and what it describes is SAP AI Core as the management and orchestration layer of an AI architecture: extending Joule Agents in SAP Joule, the model library in Joule Studio for contextual reasoning, connecting data products from SAP Business Data Cloud, and embedding AI in SAP S/4HANA. The SAP Knowledge Graph the title names does not appear in that text, so the edges rest on the abstract as published, and whether the session follows the title or the abstract is not known until it is recorded. A TechEd 2026 session (Wednesday 28 October, Berlin; also RA110V, virtual), presented by Jan Portisch and Pavithra G K, written here from SAP's abstract; the recording is not yet published.
Reimagining master data as the foundation for enterprise AIReimagining master data as the foundation for enterprise AIMaster data as the foundation for AI: SAP Business Data Cloud unifying, governing and delivering master data as reusable data products, the cataloguing and lineage concern, for analytics, autonomous applications and AI that share one business context. The abstract names no component of Business Data Cloud and no master data product, and Reltio, the co-presenter's company, is not named in it. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Arne Ludwig and Sriraj Rajaram, written here from SAP's abstract; the recording is not yet published.
Road map for SAP HANA Cloud: What’s next for the AI databaseRoad map for SAP HANA Cloud: What’s next for the AI databaseSAP's road map for SAP HANA Cloud, which the abstract places as a core component of SAP Business AI Platform within SAP Business Data Cloud. The abstract promises a firsthand look at what is next for the database and names no feature, release or date, so the two edges rest on the products it names and nothing more. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Niklas Siemer and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
SAP BDC and AI: A Perfect MatchSAP BDC and AI: A Perfect MatchA Devtoberfest 2026 data-track session (DAT-22) in which Business Data Cloud's CTO sets out how SAP Business Data Cloud feeds SAP's business AI platform: data products whose primary persistence is an object store and whose semantics are kept with them, the one domain model that links a supplier in Ariba to a supplier in S/4HANA, and the SAP knowledge graph, a triple store running in SAP HANA Cloud and queried with SPARQL, that SAP Joule consults before answering. The live demo asks Joule for the available data products and the top ten open purchase orders, with the data product query agent compiling SQL over virtual tables and a space rendering a dashboard, which is the cataloguing side of this: a central registry, the Unified Customer Landscape, that every activated data product is registered in. The Q&A covers where the knowledge graph lives and what a customer may extend, base policies that turn into filter conditions on an agent's queries, and Joule Studio as the place to build your own agents and data products.SAP Developers, published 2026-09-29
SAP BDC in Business AI Platform: Contextualize and ReasonSAP BDC in Business AI Platform: Contextualize and ReasonA Devtoberfest 2026 session (DAT-31) that places SAP Business Data Cloud as the contextualise-and-reason pillar of the SAP Business AI Platform, between the build pillar of Joule Studio and Integration Suite and the govern pillar of AI Agent Hub. It covers data products described with open resource discovery and core schema notation metadata, a data product creation agent that assembles a derived data product for overdue billing documents from the billing document and customer products and shows its lineage and fields; the data products a line-of-business application brings being readable by Joule without a BDC subscription; and the SAP-managed knowledge graph that maps business entities and their relationships for agents, held as graph data in the SAP HANA Cloud knowledge graph engine as RDF triples queried with SPARQL. The closing demo has SAP Joule answer head-count and purchase-order questions, with the generated SQL passed through a data product query that adds the restriction policy defined for that user in cloud identity services, which is why the session stands for cataloguing and lineage as much as for the products it names.SAP Developers, published 2026-10-06
SAP HANA Cloud as the AI database for SAP Business Data CloudSAP HANA Cloud as the AI database for SAP Business Data CloudSAP HANA Cloud as the AI database at the centre of SAP Business Data Cloud: the strategy behind its AI-first direction, and a Carl Zeiss speaker on how it runs in production today. The abstract names the two products and the customer and no feature, workload or figure, so the edges rest on the products as its subject. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Kush Kashyap and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Share data products with zero copies using SAP Business Data Cloud ConnectShare data products with zero copies using SAP Business Data Cloud ConnectSAP Business Data Cloud Connect shares data products between SAP Business Data Cloud and third-party platforms with zero-copy access, in both directions and for metadata as well as data, in SAP's abstract, with the business context kept on the way. The abstract names the product and its two properties, bidirectional and zero-copy, and does not say which third-party platforms or which protocol carry the sharing. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Babacar Toure, Hannes Keil, Maria Uruena and Neetha Pucknat, written here from SAP's abstract; the recording is not yet published.
Strategy and Tool Updates on BW Modernization with SAP Business Data CloudStrategy and Tool Updates on BW Modernization with SAP Business Data CloudDevtoberfest 2026 session DAT-13, in which a product manager for SAP Business Data Cloud sets out the revised BW modernisation strategy, now called optimise, modernise and innovate, and the three tools that carry it. The data product generator transfers BW InfoProviders into local table files in a dedicated BW inbound space of SAP Datasphere, where a data product is still created by hand in the data sharing cockpit; the query template generator turns BW query metadata into an analytical model template in the HANA space; the BW migration assistant, planned to start in Q4 for BW NetWeaver, takes the data flows and transformations below them, and is shown on slides only. That is the loading a warehouse edge, and the demos cover the BW/4HANA cockpit, the ABAP program for the NetWeaver GUI, mass generation with semantics from the BW modeling tools, and the flattening operator for sharing data outside SAP.SAP Developers, published 2026-09-22
The future of the SAP Business Data Cloud solution: Data and AI road mapThe future of the SAP Business Data Cloud solution: Data and AI road mapThe road map for SAP Business Data Cloud as the data foundation of SAP Business AI Platform: upcoming work in data products, AI models and agentic analytics, framed as activating business context and running autonomous processes. A road map session, so nothing in it ships yet, and the abstract names the three areas and no item within them; a Fresenius speaker co-presents. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA802V, virtual), presented by Constantin Herbst and Prakash Nanduri, written here from SAP's abstract; the recording is not yet published.
The next evolution of SAP Business Data Cloud with Dremio and SAP ReltioThe next evolution of SAP Business Data Cloud with Dremio and SAP ReltioSAP Business Data Cloud's data fabric with two additions SAP's abstract names, Dremio and SAP Reltio: data products, open catalogues, unified master data and business semantics as the pieces of a data foundation for analytics and agentic AI. The abstract names the two products and not what each takes over in the fabric. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Florian Schmidt, Rene Kirchhoff and Sriraj Rajaram, written here from SAP's abstract; the recording is not yet published.
Transform business data into AI-supported insightsTransform business data into AI-supported insightsBusiness metrics turned into insights, narratives and recommendations by SAP Joule's agents, with People Intelligence, the SAP Snowflake solution extension for SAP Business Data Cloud and SAP Analytics Cloud connected in SAP Business Data Cloud. The abstract names what is connected and what comes out, and does not say what the exercise builds or where the Snowflake extension sits in it; People Intelligence and the extension are not atlas entries. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Babacar Toure, Maximilian Paul Gander, Neetha Pucknat and San Tran, written here from SAP's abstract; the recording is not yet published.
Transforming Enterprise Data Strategy with SAP Business Data CloudTransforming Enterprise Data Strategy with SAP Business Data CloudSAP's layered picture of SAP Business Data Cloud, from lake storage and compute up to a knowledge core and agents, with eight sub-pages that each work one part through. The data products page is the cataloguing and lineage part: datasets described by Open Resource Discovery metadata, listed in the BDC catalog and shared over Delta Sharing to SAP Databricks and SAP HANA Cloud, with SAP Datasphere as a consumer on the intelligent content page; other pages install intelligent content, bring SAP BW data in through the Data Product Generator, provision groups by SCIM from Cloud Identity Services into SAP Databricks, which is identity provisioning, and train predictive models in SAP Databricks that SAP AI Core then serves for batch and real-time scoring. The main page states direction more than mechanism, and the BW page marks SQL Share for derived and OData for analytical data products as to be available.published 2026-05-12
What’s next for agentic analytics and planning in SAP Business Data CloudWhat’s next for agentic analytics and planning in SAP Business Data CloudWhat is next for agentic analytics and planning in SAP Business Data Cloud: SAP Joule's agents automating insight delivery, analysis, narrative generation and modelling tasks. A road map session; the abstract names the four kinds of task and no agent or date. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA806V, virtual), presented by Kristian Ruemmelin, written here from SAP's abstract; the recording is not yet published.
Handling Concurrent Updates in SAP CAP JavaHandling Concurrent Updates in SAP CAP JavaAlice and Bob open the same employee record; Bob saves last and quietly erases Alice's change. The lost-update problem stated concretely and then answered in CAP Java, which is the only entry here on the subject — hence the capability.Anjali_Pathak, published 2026-05-26
CAP-level Data FederationCAP-level Data FederationA Devtoberfest 2026 session (CAP-31) on letting one CAP application read another's data as if it were local. The modelling half is the same for both answers, which is why the two technical edges hold: the provider defines an API service and exports it with CDS export as an npm package carrying the model, mock data and translated texts, the consumer imports it and puts consumption views on top, and only then is it wired either as service-level replication that copies the rows into local tables each time the server starts, or over the SAP HANA synonyms that cds-federation-synonyms generates, with HDI grants on the provider side and a service replacement that redirects each synonym from its mock table to the provider's container. It is worked through on xflights and xtravels, including the local run where CDS watch mocks the imported service from the CSV files inside the package.SAP Developers, published 2026-10-02
Enhancing agentic AI with trusted business dataEnhancing agentic AI with trusted business dataHow SAP Business Data Cloud gives AI applications and agents governed access to business data and its context, and how zero-copy architectures let AI read enterprise data with less of it moved, which is the data federation concern. The abstract names the product and the architecture and states no mechanism or product the zero-copy path runs over. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA100V, virtual), presented by Aruna Kashinath, Hannes Keil and San Tran, written here from SAP's abstract; the recording is not yet published.
Federating, Replicating, and Caching Remote Data in CAP — Part 2Federating, Replicating, and Caching Remote Data in CAP — Part 2The practical half of the pair. Where Part 1 sets out the terminology, what CAP does out of the box and where the gaps are, this one builds a small application that federates, replicates and caches remote data, one step at a time, with the finished project published as sales-cockpit so a reader can either follow along or start from the end. It began as a twenty-minute reCAP talk, which the author says was only room for the intro.published 2026-07-17
The Full Picture: Federating, Replicating, and Caching Remote Data in CAP — Part 1The Full Picture: Federating, Replicating, and Caching Remote Data in CAP — Part 1Part one of two, and the concepts half: terminology, what CAP already does, and what a project still has to write. It fixes a vocabulary — federation is the umbrella for making remote data part of your model, delegation forwards each request to the remote at query time, replication is a scheduled copy into the local database, and caching is an option on either rather than a third strategy — which collides with CAP's own, since what this series calls replication is what the CAP-level Data Federation guide calls federation. From the ground the Service Integration guide covers, it lists what is left to hand-write: cross-service $expand, navigation filters across the boundary, write forwarding, timeouts and retries, then scheduling, delta detection, backoff, a guard for two app instances sharing one schedule, idempotent writes, and knowing whether the last run succeeded. That list is why the edge to cds-data-federation holds: the second half maps it onto @federation.delegate and @federation.replicate and says which package carries which part — annotations in cds-data-federation, the scheduled engine in cds-data-pipeline, response caching through cds-caching — so it is the design rationale for the annotations, not the API reference. The gap list and the plugins answering it come from the same person who maintains them; cap-replication-demo and SAP's xtravels sample are cited as the hand-written form of the same work. Part 2 is announced as a walkthrough of a demo application and is not covered here.
Under the hood of the Delta Sharing protocolUnder the hood of the Delta Sharing protocolHow a Delta Sharing server, dsserv, implements the open-source Delta Sharing protocol for zero-copy sharing: Delta tables ingested, governed and streamed live from local S3-compatible storage into cloud consumers such as Databricks. Neither the server nor the protocol is an atlas entry; the edges are to data federation, the concern zero-copy sharing answers, and to object storage, where the tables sit, and the abstract names no SAP product. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Philipp Nell, written here from SAP's abstract; the recording is not yet published.
052: 10 Minutes from Start to Launchpad052: 10 Minutes from Start to LaunchpadWalks a RAP application from a root CDS view entity through a consumption projection and its associations to a metadata extension: a facet per field group, a hidden field via UI.hidden, and a selection field on the ABAP package, all in a Customer-layer DDLX source read by the generated Fiori elements app. It then covers the parts ABAP CDS modelling and annotation stop short of — service definition and binding, generating the UI in Business Application Studio, and wiring the deployed app into the Fiori Launchpad through an IAM App and business catalog.Björn S., published 2026-09-07
A CAP Plugin for Flexible Number Range Management: cds-numberrange-pluginA CAP Plugin for Flexible Number Range Management: cds-numberrange-pluginThe author's own plugin, and the reason given for writing it is about plugins rather than about number ranges: a year of using them convinced them that this was the way to extend CAP without leaving marks on the application. Sequential document numbers are the thing it does; keeping the host project clean is the thing it argues for.abdulbasit, published 2025-06-17
Analyze and optimize ABAP Cloud model apps built on core data servicesAnalyze and optimize ABAP Cloud model apps built on core data servicesPerformance anti-patterns in data models built with ABAP CDS under ABAP Cloud applications, and the tools that find them: the abstract names ABAP cross trace, the SQL analyzer (PlanViz) in Visual Studio Code and the SAP HANA database explorer as what the session uses to follow a bottleneck from the application to the database. The anti-patterns are taken from real business applications, which is where the data modelling edge holds; which ones are shown is not in the abstract. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Ingo Braeuninger, Robert Werlich, Steffen Siegmund and Thomas Fiedler, written here from SAP's abstract; the recording is not yet published.
Beyond READ_TEXT: Decoding SAPscript Long Texts (STXL) with SQLScript in CDS/AMDPBeyond READ_TEXT: Decoding SAPscript Long Texts (STXL) with SQLScript in CDS/AMDPSTXL stores a SAPscript long text as a compressed ABAP cluster container — LZ77 plus canonical Huffman — so the only official reads are READ_TEXT, one call per text, and its mass variant READ_TEXT_TABLE, both of which ship every decompressed line to the application server and stay invisible to ABAP CDS. The author reverse-engineered that on-disk format and ported the decoder into SQLScript, wrapped in an AMDP procedure and exposed through CDS table functions, turning long texts into a joinable, filterable column read directly in the database. On ABAP 7.56 a table function needs the driver-and-filter pattern shown because a parameter cannot bind to a calling column; on ABAP 7.58/S/4HANA 2023 the same result becomes a parameter-less CDS scalar function with true filter push-down.aamelin1, published 2026-08-20
Building an Enterprise Application Using Fiori Elements and CAP - Part 1Building an Enterprise Application Using Fiori Elements and CAP - Part 1Part one of three, and it is all backend: the CAP service the UI will sit on. The author states the constraint the series works under — simple enough for someone new to the stack, without departing from the standard project layout.Farooq, published 2025-12-10
Calculating IBP Technical Week "Key Figure Date" in S/4HANA Using CDS ViewCalculating IBP Technical Week "Key Figure Date" in S/4HANA Using CDS ViewA custom ABAP CDS view entity, selecting from the standard I_CalendarDate view, to derive the first date of an SAP IBP "technical week" — the split IBP applies when a calendar week crosses a month boundary, a date S/4HANA does not expose natively. The calculated field is built with a case/when expression over dats_add_days, giving any calendar date's technical-week key figure date.bharatbajaj, published 2026-02-18
CAP-level Data FederationCAP-level Data FederationA Devtoberfest 2026 session (CAP-31) on letting one CAP application read another's data as if it were local. The modelling half is the same for both answers, which is why the two technical edges hold: the provider defines an API service and exports it with CDS export as an npm package carrying the model, mock data and translated texts, the consumer imports it and puts consumption views on top, and only then is it wired either as service-level replication that copies the rows into local tables each time the server starts, or over the SAP HANA synonyms that cds-federation-synonyms generates, with HDI grants on the provider side and a service replacement that redirects each synonym from its mock table to the provider's container. It is worked through on xflights and xtravels, including the local run where CDS watch mocks the imported service from the CSV files inside the package.SAP Developers, published 2026-10-02
CDS Associations & JoinsCDS Associations & JoinsA Devtoberfest 2026 session from SAP's performance and scalability team on what an ABAP CDS association becomes on SAP HANA, taken as an excerpt from their internal performance training. The CDS edge rests on the three ways an association is used: a path expression and an explicit join both put a left outer join into the generated view, while exposing the association leaves the view without one and adds the join only for a query that asks for its fields, which the session calls join on demand. The data modelling edge is the advice that follows and the demo under it — cardinality written as precisely as the data allows, because the optimiser trusts it, shown with a view whose missing cardinality let SELECT COUNT(*) prune the join and return 18 rows where selecting the columns returned 56, plus the left-hand, right-hand and left-outer-to-inner rewrites that correct cardinalities make possible.SAP Developers, published 2026-10-12
Create CDS Views and expose through OData service in CAPMCreate CDS Views and expose through OData service in CAPMViews defined in CDS and then exposed, which is the whole of what a small CAP service is. Written step by step from cds init onward in Business Application Studio.VenkateshMundru, published 2025-08-11
Deep Insert in SAP CAPM Using Composition and Fiori ElementsDeep Insert in SAP CAPM Using Composition and Fiori ElementsParent and children created in one transaction, which composition already gives you in the model — the post is about what Fiori elements does with it, and what the payload looks like when the UI sends both at once.published 2026-05-22
Developing authorizations for business users in SAP Business AI Platform, ABAP environmentDeveloping authorizations for business users in SAP Business AI Platform, ABAP environmentA Devtoberfest 2026 session that walks the places an authorization check has to be written when a RAP business object is implemented, which is the whole of the authorization edge: read restrictions as DCL access controls that become a filter at query time, a child entity inheriting its parent's conditions through an association, the projection layer inheriting rather than changing them, and the same check repeated on the draft side. The ABAP CDS edge holds on that draft half — until 2608 a draft query view was needed above the draft table so a DCL had something to attach to, while a draft table entity is already on CDS level and takes the DCL directly, as long as the associations used in the inherited conditions are redefined on it. Create, update and delete are then taken handler by handler, including the trap that instance authorization reads the buffer and so cannot see the new value a pre-check would reject, and the session closes on in local mode and privileged EML calls.published 2026-10-12
Explore the declarative power of status-transition flowsExplore the declarative power of status-transition flowsModelling which state a record may move to next, declaratively, rather than scattering the rule across the handlers that move it.SAP
From SEGW to @OData.publish: Expose Your CDS View as OData in S/4HANAFrom SEGW to @OData.publish: Expose Your CDS View as OData in S/4HANAWalks through exposing an ABAP CDS view as an OData service in an on-premise S/4HANA system by adding the @OData.publish: true annotation, then registering and activating the generated service in SAP Gateway (transaction /IWFND/MAINT_SERVICE) before testing it with $filter, $top and $count. It sets this against the manual route through transaction SEGW, since the annotation generates the service, its navigation properties and its OData properties straight from the CDS view without a Service Builder project.rupalipunekar1234, published 2026-07-09
Generating Adobe Form Using RAP framework OData ServicesGenerating Adobe Form Using RAP framework OData ServicesModels a RAP root view entity and consumption view over a custom sales-order table, built with ABAP CDS, and exposes it through a service definition and an OData V2 UI service binding. A separate SEGW project implements GET_STREAM to call an Adobe Form driver class and stream the rendered PDF back as the response, with a computed link field added to the CDS view so the UI can open it. The PDF is generated in the backend and returned to the calling program rather than sent straight to a printer.Megastar, published 2025-03-18
Learn how to define constraints declaratively in your CDS modelLearn how to define constraints declaratively in your CDS modelConstraints expressed in the model rather than checked in a handler — the distinction the atlas draws between input validation the framework enforces and validation somebody writes.SAP
Understanding Projections in CAPM: Select Only What You Need!Understanding Projections in CAPM: Select Only What You Need!One concept, explained by someone who had just learned it and says so — what a projection is, why it matters, and an analogy. The register is unusual here and suits the subject: projections are the first thing that makes CDS feel different from a table.Avisek_, published 2025-06-10
Updates on Embedded Analytics in ABAP Cloud for DevelopersUpdates on Embedded Analytics in ABAP Cloud for DevelopersA Devtoberfest 2026 session (ABA-33) on the generator wizards for Embedded Analytics in ABAP Cloud, run by right-clicking a data definition in the ADT Project Explorer. It first names the artefacts a star schema needs, all of them ABAP CDS — cube view at its centre, dimension, text and hierarchy views reached by association, a hierarchy directory, and an InA service definition and binding — and then generates them: the star schema generator reads a view entity's metadata, sorts its fields into dimensions and measures, asks about the ones it cannot decide, offers the dimension views it found and writes an activated cube view; the hierarchy generator produces directory, node, base and definition views plus a maintenance business object with a generated app, which is used to group airlines into alliances before the hierarchy is switched on in the layout of the multi-dimensional analysis app. That is analytic modelling on the ABAP platform, which is what the edges rest on; the outlook names time-dependent hierarchies, translatable texts and dimensions generated from database tables.published 2026-10-05
A Use Case for HANA Cloud Knowledge Graph: AI‑Driven Tender AnalysisA Use Case for HANA Cloud Knowledge Graph: AI‑Driven Tender AnalysisMatching unstructured text against internal data, using both HANA engines at once — the Knowledge Graph for the relationships and the Vector Engine for similarity — with CAP holding the application and its data. Notes that the Knowledge Graph Engine is off by default and has to be enabled when the instance is created, which is the kind of thing that stops a weekend.giacomo_dantonio, published 2026-03-19
Accelerating Your Analytics with Delta Table Replication into SAP HANA CloudAccelerating Your Analytics with Delta Table Replication into SAP HANA CloudStarting with QRC 04/2025, SAP HANA Cloud can replicate a Delta Lake table from an external Delta Sharing source directly into a native HANA table, rather than only querying it live through a virtual table. The post walks through creating a remote subscription, running a chunk-based initial load, and setting up change data capture on a schedule or on demand, each with the SQL statements and monitoring views involved, plus the simpler virtual-table-toggling and HANA Cloud Central UI alternatives.SeungjoonLee, published 2025-12-22
Agentic memory: Knowledge graph engine and recall in SAP HANA CloudAgentic memory: Knowledge graph engine and recall in SAP HANA CloudThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA263 on Wednesday 28 October is a two-hour hands-on on the same engine with a different cast. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Markus Fath and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
Analyze and optimize ABAP Cloud model apps built on core data servicesAnalyze and optimize ABAP Cloud model apps built on core data servicesPerformance anti-patterns in data models built with ABAP CDS under ABAP Cloud applications, and the tools that find them: the abstract names ABAP cross trace, the SQL analyzer (PlanViz) in Visual Studio Code and the SAP HANA database explorer as what the session uses to follow a bottleneck from the application to the database. The anti-patterns are taken from real business applications, which is where the data modelling edge holds; which ones are shown is not in the abstract. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Ingo Braeuninger, Robert Werlich, Steffen Siegmund and Thomas Fiedler, written here from SAP's abstract; the recording is not yet published.
Automate Recurring Data Updates in SAP HANA CloudAutomate Recurring Data Updates in SAP HANA CloudA walkthrough for marking inventory rows stale after 30 days using SAP HANA Cloud's own scheduler: a SQLScript procedure, a CREATE SCHEDULER JOB statement with its 7-field cron pattern, the M_SCHEDULER_JOBS monitoring view, and the matching DROP statements to remove both. It then names where that approach stops and lists the alternatives for scheduling outside the database: SAP Integration Suite's Timer Event, the SAP Job Scheduling service, SAP Automation Pilot for infrastructure commands, and a custom approach for triggering scheduled REST calls from an application.Joni, published 2026-06-11
Bridging Python and SAP HANA: Inside the sqlalchemy-hana Open-Source DialectBridging Python and SAP HANA: Inside the sqlalchemy-hana Open-Source DialectA Devtoberfest 2026 data-track session (DAT-21) in which one of the maintainers of sqlalchemy-hana, the open-source SQLAlchemy dialect published in SAP's GitHub organisation, opens up what sits between Python and SAP HANA. It walks the five dialect classes that render statements, types, DDL, identifiers and sequences, and the HANA specifics they absorb: the FROM DUMMY a bare SELECT needs, a limit injected when only an offset is given, string compiled to NVARCHAR, and quoted case-sensitive identifiers against Python's lowercase. The rest covers schema migrations with Alembic on HANA's transactional DDL, the recently added async support and vector types, and that HANA Cloud and HANA 2 are supported while HANA 1 is not.SAP Developers, published 2026-09-29
Bring "developers.sap.com" Into Your Dev Environment: SAP Developer Context for AI Coding AgentsBring "developers.sap.com" Into Your Dev Environment: SAP Developer Context for AI Coding AgentsDevtoberfest 2026 session FA-11: a tour of the rebuilt developers.sap.com by the team that runs it, from the administration screens behind the home page to the agent interfaces in front of it. The site is a CAP application on SAP HANA Cloud and SAP BTP, open-sourced in full, and the half of the session that places it here is how its content reaches an agent: every tutorial is also served as markdown, a coding agent is detected and given that version instead of the HTML, a well-known agent card advertises what the site offers, and SAP Developers MCP answers questions about tutorials, news and a reader's own completion history in Claude Code and Joule Desktop, over OAuth or a personal access token. Behind the answers sit two things working together: a knowledge graph in the HANA database over 1400 tutorials and 11,000 concepts, and SAP AI Core for the Joule interactions and the embeddings, with the agent harness written for the site rather than taken off a shelf. Where neither MCP nor A2A is available, the same content is published as skills.SAP Developers, published 2026-09-25
Build AI agents and applications natively on SAP HANA CloudBuild AI agents and applications natively on SAP HANA CloudSAP HANA Cloud as the base for agentic applications on SAP Business AI Platform: the session goes through CAP, the SAP HANA Cloud vector engine and SAP AI Core, with architecture patterns and lessons learned from building AI-supported applications. SAP's abstract names the three parts of that stack and the vector engine as the database's feature in it, and describes none of the patterns. A TechEd 2026 session (Wednesday 28 October, Berlin; also DA113V, virtual), presented by Christoph Morgen and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
Build your custom knowledge layer with SAP HANA CloudBuild your custom knowledge layer with SAP HANA CloudSAP HANA Cloud's multi-model engines, the knowledge graph engine among them, as the base for a custom knowledge layer over the enterprise's data, with SAP Business Data Cloud as the product that includes the database. Graph, spatial and document data put to an AI use; the abstract names the graph engine and not the query language or the vector side. A TechEd 2026 session (Wednesday 28 October, Berlin; also ST108V, virtual), presented by Niklas Siemer and Sebastian Schmidt, written here from SAP's abstract; the recording is not yet published.
Building a CAP App with Fiori Integration – Part 1: Environment & HANA Cloud SetupBuilding a CAP App with Fiori Integration – Part 1: Environment & HANA Cloud SetupA trial account taken from nothing to a CAPM project with a HANA Cloud instance behind it. Everything here is prerequisites, which the author says outright — the application is in the parts that follow.SuryaRamesh, published 2026-04-08
Building agentic applications with SAP HANA CloudBuilding agentic applications with SAP HANA CloudA CAP application extended with semantic search and agent features on top of SAP HANA Cloud's vector engine and SAP AI Core, built in a hands-on workshop. The abstract names the parts, CAP, the vector engine and AI Core, and the two additions: semantic search, the retrieval half of retrieval-augmented generation, and LLM-supported agent capabilities inside the application, which is agent tooling. Which embedding model, which CAP runtime and how the agent calls its tools are not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hui Li, Ritty Joseph, Shraddha Shetty and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
Building an SAP BTP Agent Architecture from Scratch: Python + CAP + HANABuilding an SAP BTP Agent Architecture from Scratch: Python + CAP + HANAA first-person build log of a Flask orchestrator on Cloud Foundry that reduces a question to keywords, searches a Node.js service's Documents entity, and passes what it finds to Claude for a grounded answer. Getting there means learning that HANA's fuzzy .search() matches one word but not a full sentence, fixed by splitting the query into terms and merging the per-term hits, and that provisioning SAP HANA Cloud hits a database-level free-tier quota rather than an HDI-container one, with a stopped instance needing to be resumed first. It also covers @sap/cds-dk needing to sit in dependencies rather than devDependencies, since Cloud Foundry's buildpack skips the latter, before cds deploy --to hana can run as part of the push.neilaspin, published 2026-07-28
Building your knowledge graph on SAP HANA CloudBuilding your knowledge graph on SAP HANA CloudDevtoberfest 2026 session DAT-11, in which two enterprise architects explain what a knowledge graph is and then build one on SAP HANA Cloud. The first half sets the join across three relational tables against an ontology of classes and predicates, the subject-predicate-object triple written as a turtle file, and a SPARQL query over it, and argues that the chain of relationships is what makes a recommendation traceable back to its reasons. The demo, taken from a Discovery Center mission, curates the ontology and the RDF files for an accounts receivable scenario in VS Code, ingests the triples into HANA Cloud with SQL and walks the resulting graph outward from a customer; that is the graph, spatial and document data edge. It closes by separating three things that share the name: the HANA Cloud knowledge graph engine, SAP Knowledge Graph as the data, and the knowledge graph in SAP Business Data Cloud.SAP Developers, published 2026-09-22
CAP Foundry: Engineering SAP CAP Applications from Business Intent with Guardrailed AICAP Foundry: Engineering SAP CAP Applications from Business Intent with Guardrailed AICAP Foundry is a prototype that generates a CAP Node.js project with SAP Fiori elements from a written business requirement, discovering the actual data shape from a chosen source — SQLite, a configured SAP HANA HDI container, offline EDMX, live OData through the SAP Destination service, or approved SAP BTP ABAP objects — instead of inventing one. The generated application can carry a Fiori draft lifecycle with optimistic concurrency via ETags and annotation-driven Fiori elements list and object screens, localized independently of the underlying service contract. Attachments can be added with upload, download and delete, gated on a malware-scan status, and the generated project still has to compile, build and pass its generated tests before the run is accepted.Shahid, published 2026-08-20
CAP in the age of AI #6 - vector embeddingsCAP in the age of AI #6 - vector embeddingsVector embeddings put to work in the incident management sample, answering whether this problem has been seen before. An embedding element of type Vector is calculated and stored from the vector_embedding function, so the database refreshes it whenever the text behind it changes, and cosine_similarity compares it with a freshly embedded string; because a title says little, a scheduled action first summarises each incident's conversation through a model on SAP AI Core and the embedding is taken from that summary. The similar-incidents list is a view joining incidents to themselves, with order and limit set in a before handler on the expanded query, and the vector element excluded from the service, since OData knows nothing about vectors — on SAP HANA Cloud the function is native, while SQLite needs packages added to the project.published 2026-10-09
CAP in the age of AI #7 - vector embeddings wrap-upCAP in the age of AI #7 - vector embeddings wrap-upThe same embeddings model taken from SQLite to SAP HANA Cloud, then handed to an agent. Locally it is @cap-js/ai that adds the vector functions SQLite lacks and downloads an all-MiniLM L6v2 ONNX model on first start; on HANA natural language processing has to be switched on, the model name is a mandatory argument, the vectors it returns are 768 dimensions, and dimensions must match on both sides of a comparison. HANA itself can be given SAP AI Core as a remote source for other embedding models, which a CDS.ql expression has to inject because the postfix notation only takes what the CDS model holds, and the hour ends with a search function over cosine similarity exposed over @cap-js/mcp, so an agent asked about low output from solar panels calls semantic search instead of writing the query itself.published 2026-10-16
CAPM Basics - Part 2CAPM Basics - Part 2Walks through deploying a CAP application to SAP BTP, Cloud Foundry Runtime: provisioning a SAP HANA Cloud instance and HDI container, then running cds add hana and cds add xsuaa --for production, cds build --production, and an MTA build and deploy. Tests the deployed service in Postman with an OAuth 2.0 client credentials token from the XSUAA binding (SAP Authorization and Trust Management service), explicitly leaving out any role templates or scopes.archisman92, published 2025-02-28
Combining AI Agents with the power of SAP HANA embedded ML (part 1)Combining AI Agents with the power of SAP HANA embedded ML (part 1)Devtoberfest 2026 session DAT-12, the first of two parts, in which Vitaliy Rudnytskiy does a data scientist's work against the embedded machine learning of SAP HANA Cloud by talking to an agent. The session first takes an agent apart into its LLM, its tools, its memory and the loop between them, then stacks the Predictive Analysis Library under the hana-ml Python wrapper and that under the HANA AI toolkit, whose tools an agent calls from plain English in a notebook to preview a sales refunds table, split it into train and predict tables, run a time-series check and train an AutoML forecast, keeping what it decided in Markdown memory files. That is the agent tooling edge; the same toolkit is then started as an MCP server over stdio and over streamable HTTP and reached from a coding agent and from Joule Work's desktop, which is where the live demo partly fails and the failure is shown.published 2026-09-22
Connect SAP CAP (Node.js) to On-Premise/Private PostgreSQL using SAP Cloud ConnectorConnect SAP CAP (Node.js) to On-Premise/Private PostgreSQL using SAP Cloud ConnectorAn end-to-end route from a CAP Node.js application on Cloud Foundry to a PostgreSQL database that is never made publicly reachable, over BTP Connectivity and the Cloud Connector using a TCP destination and SOCKS5. The part worth having is that it covers the deployer as well as the server: the generated PostgreSQL deployer has to reach the same private database to deploy the CDS model, and a guide that only connects the runtime leaves you with a schema you cannot install.Kalaikovan, published 2026-08-07
Connect SAP CAP (Node.js) to On-Premise/Private PostgreSQL using SAP Cloud Connector
Database connectors changed in @sap/cds 10.1.0, 2026-09-07. Affects A recipe.
Create a CAP Application with SAP HANA Cloud from Scratch and Deploy to Cloud FoundryCreate a CAP Application with SAP HANA Cloud from Scratch and Deploy to Cloud FoundryThe whole lifecycle in one post rather than a series — model, service, HANA binding, build, deploy. Useful as a single reference for the order things have to happen in, which is the part that is easy to get wrong when it is spread over six posts.MaheshSirsat1708, published 2025-11-19
Create a CAP Application with SAP HANA Cloud from Scratch and Deploy to Cloud Foundry
Database connectors changed in @sap/cds 10.1.0, 2026-09-07. Affects A recipe.
Creating a Hybrid CAP (Node.js) Profile with PostgreSQL on BTP from Business Application StudioCreating a Hybrid CAP (Node.js) Profile with PostgreSQL on BTP from Business Application StudioHybrid testing is documented for HANA; this is the same profile against a PostgreSQL instance on BTP, driven from a BAS dev space rather than a laptop. Proposed under editor support because of where it runs, but the subject is the binding: what cds bind writes, and what has to be true of the service instance and the tunnel for a local process to reach it.valentincadart, published 2025-10-02
Creating a Hybrid CAP (Node.js) Profile with PostgreSQL on BTP from Business Application Studio
Database connectors changed in @sap/cds 10.1.0, 2026-09-07. Affects Runnable code.
Flexible analytics at speed: Calculation views in SAP Business Data CloudFlexible analytics at speed: Calculation views in SAP Business Data CloudCalculation views in SAP HANA Cloud, the reusable analytic modelling blocks built in its graphical modelling environment, with three newer parts the abstract names: AI-assisted modelling, refactoring, and advanced materialisation, and the way the views sit inside SAP Business Data Cloud. What a materialisation is chosen on, and what the AI assistance generates, is not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hansika Colomboge Dona, Jan Zwickel, Niklas Siemer and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-1]Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-1]The first of six, and it does the thing the later parts depend on: build the Incident Management application against SQLite on a laptop, with no cloud database in sight. The series is called decoupled because the front end and the back end are deployed separately, and this part is entirely the back end.sanjucs, published 2026-05-06
Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-1]
Database connectors changed in @sap/cds 10.1.0, 2026-09-07. Affects A recipe, Runnable code.
Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-3]Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-3]The cloud database appears: a HANA Cloud instance created on BTP and mapped to a Cloud Foundry space. No application code — this is the part where the platform has to be right before the next part can connect to it.sanjucs, published 2026-05-08
Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-4]Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-4]The switch from SQLite to HANA and the first deploy of the back end to Cloud Foundry — the point in the series where the persistence stops being a file and the build starts producing HDI artifacts.sanjucs, published 2026-05-12
Fullstack CAP Application with HANA Cloud (Decoupled Architecture) [Part-4]
Database connectors changed in @sap/cds 10.1.0, 2026-09-07. Affects A recipe.
Get hands on with tabular AI and forecasting models in SAP HANA CloudGet hands on with tabular AI and forecasting models in SAP HANA CloudPrediction and forecasting as predictive models inside SAP HANA Cloud, worked through hands-on: tabular AI models such as SAP-RPT-1 for on-the-fly predictions, time series foundation models for ad hoc forecasts, and the AutoML in the predictive analysis library. The abstract names the model kinds and the library and does not say how a model is called from SQL or from an application. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Markus Fath, Ritty Joseph and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
Knowledge graph and agent memory: Build an agent that remembersKnowledge graph and agent memory: Build an agent that remembersThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA205 on Tuesday 27 October is the 45-minute talk on the same engine, with a near-identical abstract and a different cast. A two-hour hands-on TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Jan Zwickel, Markus Fath and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Lets Talk to the Database - CAP & SQLite Powered by Google Gemini-2.5-ProLets Talk to the Database - CAP & SQLite Powered by Google Gemini-2.5-ProNatural language against a CAP service on SQLite, with a non-SAP model doing the translation. Written as a learning exercise rather than a pattern, and the choice of Gemini over anything in the AI hub is the interesting part of it.ShivamShuklaSAP, published 2025-04-16
Medallion Reference Architecture for Big Data Processing in SAP HANA CloudMedallion Reference Architecture for Big Data Processing in SAP HANA CloudSAP's medallion layout for SAP HANA Cloud: structured, semi-structured and unstructured data lands raw in HANA Cloud, data lake files as the bronze layer, is cleansed into a common structure in silver, held in data lake files or the HANA database, and is curated and read-optimised in gold, from where it can also be exposed as a Delta Share. The staged path from raw to consumable is the ground loading a warehouse covers, with Spark jobs and SAP Datasphere data flows named as ways to move data between layers and SAP Analytics Cloud among the consumers of gold. It leaves the ingestion method open, to be chosen by source, freshness and performance, and names no pipeline or schedule beyond that.published 2025-04-03
Modernize your database landscape with SAP HANA CloudModernize your database landscape with SAP HANA CloudWhy to move a database estate to SAP HANA Cloud, and the migration tools and services for doing so, which is the platform migration concern. SAP's abstract is one sentence and names none of the tools. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Niklas Siemer and Roman Belosludtsev, written here from SAP's abstract; the recording is not yet published.
Part 1: Creating and Deploying a SAP CAP Application with SAP HANA on SAP BTP (Cloud Foundry)Part 1: Creating and Deploying a SAP CAP Application with SAP HANA on SAP BTP (Cloud Foundry)Opens with the observation the whole series rests on — CAP is usually demonstrated locally, and the interesting part starts when it is deployed. Part one of the run that continues into PostgreSQL and Work Zone.yashbhosle789, published 2026-02-25
Part 1: Creating and Deploying a SAP CAP Application with SAP HANA on SAP BTP (Cloud Foundry)
Database connectors changed in @sap/cds 10.1.0, 2026-09-07. Affects A recipe.
Part 2: Creating and Deploying a CAP Application with PostgreSQL, Hyperscaler OptionPart 2: Creating and Deploying a CAP Application with PostgreSQL, Hyperscaler OptionThe middle of a series that runs from database to Work Zone: the CAP application from part one pointed at PostgreSQL on the hyperscaler option, and deployed. The service binding and the build are where it spends its time.yashbhosle789, published 2026-03-04
Part 2: Creating and Deploying a CAP Application with PostgreSQL, Hyperscaler Option
Database connectors changed in @sap/cds 10.1.0, 2026-09-07. Affects A recipe.
Road map for SAP HANA Cloud: What’s next for the AI databaseRoad map for SAP HANA Cloud: What’s next for the AI databaseSAP's road map for SAP HANA Cloud, which the abstract places as a core component of SAP Business AI Platform within SAP Business Data Cloud. The abstract promises a firsthand look at what is next for the database and names no feature, release or date, so the two edges rest on the products it names and nothing more. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Niklas Siemer and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
SAP BDC in Business AI Platform: Contextualize and ReasonSAP BDC in Business AI Platform: Contextualize and ReasonA Devtoberfest 2026 session (DAT-31) that places SAP Business Data Cloud as the contextualise-and-reason pillar of the SAP Business AI Platform, between the build pillar of Joule Studio and Integration Suite and the govern pillar of AI Agent Hub. It covers data products described with open resource discovery and core schema notation metadata, a data product creation agent that assembles a derived data product for overdue billing documents from the billing document and customer products and shows its lineage and fields; the data products a line-of-business application brings being readable by Joule without a BDC subscription; and the SAP-managed knowledge graph that maps business entities and their relationships for agents, held as graph data in the SAP HANA Cloud knowledge graph engine as RDF triples queried with SPARQL. The closing demo has SAP Joule answer head-count and purchase-order questions, with the generated SQL passed through a data product query that adds the restriction policy defined for that user in cloud identity services, which is why the session stands for cataloguing and lineage as much as for the products it names.SAP Developers, published 2026-10-06
SAP CAP Lessons Learned: SQLite is single threaded, HANA is notSAP CAP Lessons Learned: SQLite is single threaded, HANA is notA page long, and one of the more useful pages here: the local database serialises what the deployed one runs in parallel, so concurrency bugs are invisible until they are not. Filed by the author as something the tutorials do not make clear.LucasMagriniRigo, published 2025-01-22
SAP CAP on HANA XSA: Scaling Industrial Data Applications Beyond the CloudSAP CAP on HANA XSA: Scaling Industrial Data Applications Beyond the CloudCAP on HANA 2.0 XSA rather than on BTP — on-premise, and chosen for throughput. Mass ingestion through native stored procedures, which is the point at which CDS stops being the right tool and the post says so.rgadirov, published 2026-03-09
SAP CAP on HANA XSA: Scaling Industrial Data Applications Beyond the Cloud
Database connectors changed in @sap/cds 10.1.0, 2026-09-07. Affects Runnable code.
SAP CAP With Prostgres Serice in BTPSAP CAP With Prostgres Serice in BTPA step-by-step walkthrough of a CAP bookshop project on @cap-js/postgres, provisioning PostgreSQL on SAP BTP, hyperscaler option's trial plan through mta.yaml, building the MTA archive and deploying it to Cloud Foundry by hand, then inspecting the deployed database with pgAdmin over an SSH tunnel. It updates an earlier post by Mike Zaschka on the same topic to the package CAP now ships by default, though the manual build-and-deploy sequence it shows predates cds up folding those steps into one command by a day.satya-dev, published 2025-03-30
SAP HANA Cloud advisors and automationSAP HANA Cloud advisors and automationSAP HANA Cloud's advisors and the tasks they hand off: the elastic compute node, the partition, index and native storage extension advisors that produce recommendations for performance and efficiency, and SAP Automation Pilot as the service that runs the resulting tasks, which is operations automation on the database. The abstract lists the features and stops there, so what each advisor recommends and how a recommendation becomes an Automation Pilot command is not stated. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Hansika Colomboge Dona, Hui Li, Javier Martin and Roman Belosludtsev, written here from SAP's abstract; the recording is not yet published.
SAP HANA Cloud as a self-managed database: Advisors and automationSAP HANA Cloud as a self-managed database: Advisors and automationSAP HANA Cloud advisors generate recommendations for database administration, aimed at system performance and efficiency, and SAP Automation Pilot runs the manual and administrative tasks around the database as automated processes, which is the operations automation concern on the database side. SAP's abstract names the two services and claims reduced operational overhead; which advisors exist and which tasks the automation covers are not said. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Javier Martin and Roman Belosludtsev, written here from SAP's abstract; the recording is not yet published.
SAP HANA Cloud as an Esri GeodatabaseSAP HANA Cloud as an Esri GeodatabaseSAP's design for running an Esri ArcGIS Enterprise geodatabase inside SAP HANA Cloud, so that geometries and SAP business data sit in one database and are joined in a HANA calculation view, which is the spatial part of graph, spatial and document data. It traces three personas: an analyst in ArcGIS Pro building query layers over that view, a developer whose CAP application models spatial types such as ST_Point in CDS, and an analyst using a Fiori app on top of such an application. The deployment advice stops at placement: ArcGIS Server and HANA Cloud go in the same region and availability zone, because Esri's certified architectures allow under 5 milliseconds of network latency between them.published 2025-03-25
SAP HANA Cloud as the AI database for SAP Business Data CloudSAP HANA Cloud as the AI database for SAP Business Data CloudSAP HANA Cloud as the AI database at the centre of SAP Business Data Cloud: the strategy behind its AI-first direction, and a Carl Zeiss speaker on how it runs in production today. The abstract names the two products and the customer and no feature, workload or figure, so the edges rest on the products as its subject. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Kush Kashyap and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
SAP HANA Cloud: The data foundation for contextualizing and reasoningSAP HANA Cloud: The data foundation for contextualizing and reasoningWhere SAP is taking SAP HANA Cloud, described in the abstract as the anchor of SAP's data strategy and a unified layer to store, contextualise and reason across a business, and what that means for a data platform decision. The abstract is a direction statement and names no feature, release or date, so the one edge rests on the product itself. A TechEd 2026 session (Tuesday 27 October, Berlin; also ST106V, virtual), presented by Matthew Zenus and Stefan Baeuerle, written here from SAP's abstract; the recording is not yet published.
SAP HANA Data Lake Files (HDLF) Basic FunctionalitiesSAP HANA Data Lake Files (HDLF) Basic FunctionalitiesA Devtoberfest 2026 data-track session on SAP HANA data lake files, the managed object store inside SAP HANA Cloud that is provisioned from HANA Cloud Central, priced per API call and per stored gigabyte, and reached with the same REST API whichever hyperscaler it runs on. Two product managers set up an instance with its IP allow list, client certificates and trusts, then upload, list, read and delete files over the WebHDFS REST API and the HDLFS command-line utility — the Object storage half — and cover file versions with snapshots, access policies per file, and chunked upload with a server-side merge. They then link the instance to a HANA database and query a CSV file as a virtual table: SQL on files now runs through a file adapter in the database, while the older path through the data lake relational engine is deprecated.SAP Developers
Setting Up PostgreSQL for SAP BTP Development: A Practical GuideSetting Up PostgreSQL for SAP BTP Development: A Practical GuideOpens with the premise the rest of this bucket mostly assumes away — not every BTP application needs HANA Cloud — and then sets up PostgreSQL on the hyperscaler option. Part one of a series that continues into XSUAA.michal_majer, published 2026-01-20
Stop guessing, start counting: How generative AI fixed an inventory messStop guessing, start counting: How generative AI fixed an inventory messAn inventory-counting application a business built on SAP Business AI Platform with SAP HANA Cloud and generative AI, to replace recount lists kept by gut feel across SAP ERP Central Component, SAP S/4HANA and Microsoft Excel; the talk promises the app, its architecture and what went wrong. The generative AI part is LLM integration from application code; the abstract names HANA Cloud and generative AI as the two building blocks and says nothing about how either is used. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Ranjeet Kumar, written here from SAP's abstract; the recording is not yet published.
Talking to your database: The new data exploration tools in SAP HANA CloudTalking to your database: The new data exploration tools in SAP HANA CloudSAP HANA Cloud's new data exploration tools take a business question in plain language, find the right database objects and run the query, with no data model and no SQL written beforehand, shown live on a standard business data set. SAP's abstract says the session covers how the tools work, what they need and where they hit their limits, and states none of the three. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Anna Hartmann, written here from SAP's abstract; the recording is not yet published.
Unlock predictive and generative AI with your data in SAP HANA CloudUnlock predictive and generative AI with your data in SAP HANA CloudThe AI features SAP lists for SAP HANA Cloud: the function libraries for tabular prediction and forecasting, where predictive models run inside the database, the vector engine, the knowledge graph engine, which is graph, spatial and document data put to generative use, and SQL to LLM calls. The abstract names the engines and the use cases they are meant for and gives no detail of any one of them. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA204V, virtual), presented by Christoph Morgen and Javier Martin, written here from SAP's abstract; the recording is not yet published.
Use SAP HANA as the Database for a CAP Java ApplicationUse SAP HANA as the Database for a CAP Java ApplicationMoving a CAP Java application off the development database onto HANA, which is the step where the persistence choice stops being invisible.SAP
Using HANA Cloud’s "VECTOR_EMBEDDING" Function in CAPUsing HANA Cloud’s "VECTOR_EMBEDDING" Function in CAPEmbeddings generated inside the database rather than fetched from AI Core or an external model — a Q4 2024 HANA Cloud function, used from CAP. The shift it describes is where the embedding step lives, which changes what has to be deployed and what has to be called.published 2025-03-02
Agentic memory: Knowledge graph engine and recall in SAP HANA CloudAgentic memory: Knowledge graph engine and recall in SAP HANA CloudThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA263 on Wednesday 28 October is a two-hour hands-on on the same engine with a different cast. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Markus Fath and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
Build your custom knowledge layer with SAP HANA CloudBuild your custom knowledge layer with SAP HANA CloudSAP HANA Cloud's multi-model engines, the knowledge graph engine among them, as the base for a custom knowledge layer over the enterprise's data, with SAP Business Data Cloud as the product that includes the database. Graph, spatial and document data put to an AI use; the abstract names the graph engine and not the query language or the vector side. A TechEd 2026 session (Wednesday 28 October, Berlin; also ST108V, virtual), presented by Niklas Siemer and Sebastian Schmidt, written here from SAP's abstract; the recording is not yet published.
Building your knowledge graph on SAP HANA CloudBuilding your knowledge graph on SAP HANA CloudDevtoberfest 2026 session DAT-11, in which two enterprise architects explain what a knowledge graph is and then build one on SAP HANA Cloud. The first half sets the join across three relational tables against an ontology of classes and predicates, the subject-predicate-object triple written as a turtle file, and a SPARQL query over it, and argues that the chain of relationships is what makes a recommendation traceable back to its reasons. The demo, taken from a Discovery Center mission, curates the ontology and the RDF files for an accounts receivable scenario in VS Code, ingests the triples into HANA Cloud with SQL and walks the resulting graph outward from a customer; that is the graph, spatial and document data edge. It closes by separating three things that share the name: the HANA Cloud knowledge graph engine, SAP Knowledge Graph as the data, and the knowledge graph in SAP Business Data Cloud.SAP Developers, published 2026-09-22
Knowledge graph and agent memory: Build an agent that remembersKnowledge graph and agent memory: Build an agent that remembersThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA205 on Tuesday 27 October is the 45-minute talk on the same engine, with a near-identical abstract and a different cast. A two-hour hands-on TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Jan Zwickel, Markus Fath and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
SAP BDC in Business AI Platform: Contextualize and ReasonSAP BDC in Business AI Platform: Contextualize and ReasonA Devtoberfest 2026 session (DAT-31) that places SAP Business Data Cloud as the contextualise-and-reason pillar of the SAP Business AI Platform, between the build pillar of Joule Studio and Integration Suite and the govern pillar of AI Agent Hub. It covers data products described with open resource discovery and core schema notation metadata, a data product creation agent that assembles a derived data product for overdue billing documents from the billing document and customer products and shows its lineage and fields; the data products a line-of-business application brings being readable by Joule without a BDC subscription; and the SAP-managed knowledge graph that maps business entities and their relationships for agents, held as graph data in the SAP HANA Cloud knowledge graph engine as RDF triples queried with SPARQL. The closing demo has SAP Joule answer head-count and purchase-order questions, with the generated SQL passed through a data product query that adds the restriction policy defined for that user in cloud identity services, which is why the session stands for cataloguing and lineage as much as for the products it names.SAP Developers, published 2026-10-06
SAP HANA Cloud as an Esri GeodatabaseSAP HANA Cloud as an Esri GeodatabaseSAP's design for running an Esri ArcGIS Enterprise geodatabase inside SAP HANA Cloud, so that geometries and SAP business data sit in one database and are joined in a HANA calculation view, which is the spatial part of graph, spatial and document data. It traces three personas: an analyst in ArcGIS Pro building query layers over that view, a developer whose CAP application models spatial types such as ST_Point in CDS, and an analyst using a Fiori app on top of such an application. The deployment advice stops at placement: ArcGIS Server and HANA Cloud go in the same region and availability zone, because Esri's certified architectures allow under 5 milliseconds of network latency between them.published 2025-03-25
Unlock predictive and generative AI with your data in SAP HANA CloudUnlock predictive and generative AI with your data in SAP HANA CloudThe AI features SAP lists for SAP HANA Cloud: the function libraries for tabular prediction and forecasting, where predictive models run inside the database, the vector engine, the knowledge graph engine, which is graph, spatial and document data put to generative use, and SQL to LLM calls. The abstract names the engines and the use cases they are meant for and gives no detail of any one of them. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA204V, virtual), presented by Christoph Morgen and Javier Martin, written here from SAP's abstract; the recording is not yet published.
Explore your Hyperscaler data with SAP Business Data CloudExplore your Hyperscaler data with SAP Business Data CloudSAP's map of the ways data held on hyperscaler and partner platforms is joined with SAP data in SAP Business Data Cloud, with a sub-page each for AWS, Azure, Google Cloud, Databricks and Snowflake. It sets four modes side by side: BDC Connect shares data products in both directions over the Delta Sharing protocol from the object store layer, while in the SAP Datasphere layer federation reads remote tables in place, Replication Flows copy SAP data out to stores such as Amazon S3 or Google BigQuery, and Data Flows import files and transform them into Datasphere tables, the last three being the ground loading a warehouse covers. The Snowflake and BigQuery connectors are dated to 2026 releases, and a closing page lists what slows federation, from source and tenant in different regions to queries that do not filter and aggregate at the source.published 2026-05-08
Medallion Reference Architecture for Big Data Processing in SAP HANA CloudMedallion Reference Architecture for Big Data Processing in SAP HANA CloudSAP's medallion layout for SAP HANA Cloud: structured, semi-structured and unstructured data lands raw in HANA Cloud, data lake files as the bronze layer, is cleansed into a common structure in silver, held in data lake files or the HANA database, and is curated and read-optimised in gold, from where it can also be exposed as a Delta Share. The staged path from raw to consumable is the ground loading a warehouse covers, with Spark jobs and SAP Datasphere data flows named as ways to move data between layers and SAP Analytics Cloud among the consumers of gold. It leaves the ingestion method open, to be chosen by source, freshness and performance, and names no pipeline or schedule beyond that.published 2025-04-03
SAP Datasphere Integration Patterns: Lessons Learned from Two Years of ImplementationsSAP Datasphere Integration Patterns: Lessons Learned from Two Years of ImplementationsTwo years of production SAP Datasphere integrations across SAP and non-SAP sources, settling on Replication Flows over remote access for high-volume Finance analytics because remote queries added latency at query time, then tuning the copy with Datasphere-side partitioning, source-side CDS view optimisation and Cloud Connector sizing. For file-based and Kafka sources, SAP Integration Suite iFlows did work a direct connection could not — flattening nested JSON, PGP decryption and orchestrating the SAP Ariba extraction built on SAP's own BTP Procurement Data Extractor content.saikrishna_kalivarapu2, published 2026-08-17
Strategy and Tool Updates on BW Modernization with SAP Business Data CloudStrategy and Tool Updates on BW Modernization with SAP Business Data CloudDevtoberfest 2026 session DAT-13, in which a product manager for SAP Business Data Cloud sets out the revised BW modernisation strategy, now called optimise, modernise and innovate, and the three tools that carry it. The data product generator transfers BW InfoProviders into local table files in a dedicated BW inbound space of SAP Datasphere, where a data product is still created by hand in the data sharing cockpit; the query template generator turns BW query metadata into an analytical model template in the HANA space; the BW migration assistant, planned to start in Q4 for BW NetWeaver, takes the data flows and transformations below them, and is shown on slides only. That is the loading a warehouse edge, and the demos cover the BW/4HANA cockpit, the ABAP program for the NetWeaver GUI, mass generation with semantics from the BW modeling tools, and the flattening operator for sharing data outside SAP.SAP Developers, published 2026-09-22
Connecting Two SAP CAP Projects Without Duplicating Your DataConnecting Two SAP CAP Projects Without Duplicating Your DataCross-container HDI synonyms, argued from the alternatives rather than presented as a recipe: copying the table, standing up an API, or hard-coding the values are the three things the author reports seeing teams do, and each is named as working but unclean. With synonyms in place the consuming project queries the owner's HANA tables through ordinary SQL and ordinary CAP service code, with no replication and nothing to drift between environments. Covers the same ground as Mio Yasutake's 2021 post from a different angle — that one enumerates four topologies, this one argues for one of them.Inderpreet, published 2026-07-08
Integrating Using Google Cloud Storage Adapter (GCP Authentication & adapter config)Integrating Using Google Cloud Storage Adapter (GCP Authentication & adapter config)Walks through connecting SAP Integration Suite's Google Cloud Storage adapter to a bucket: creating a GCP service account with the Storage Object Admin role, generating its JSON or P12 key, converting it into a key-pair alias, and using that alias and the service account email in the adapter's authentication. It covers configuring the receiver adapter's upload operation (directory, object name, content type, and override, ignore or fail handling for an existing file) and the sender adapter's read, including post-processing to archive, delete or keep the object after an iFlow fetches it.MirunaliniV, published 2026-02-20
SAP HANA Data Lake Files (HDLF) Basic FunctionalitiesSAP HANA Data Lake Files (HDLF) Basic FunctionalitiesA Devtoberfest 2026 data-track session on SAP HANA data lake files, the managed object store inside SAP HANA Cloud that is provisioned from HANA Cloud Central, priced per API call and per stored gigabyte, and reached with the same REST API whichever hyperscaler it runs on. Two product managers set up an instance with its IP allow list, client certificates and trusts, then upload, list, read and delete files over the WebHDFS REST API and the HDLFS command-line utility — the Object storage half — and cover file versions with snapshots, access policies per file, and chunked upload with a server-side merge. They then link the instance to a HANA database and query a CSV file as a virtual table: SQL on files now runs through a file adapter in the database, while the older path through the data lake relational engine is deprecated.SAP Developers
Under the hood of the Delta Sharing protocolUnder the hood of the Delta Sharing protocolHow a Delta Sharing server, dsserv, implements the open-source Delta Sharing protocol for zero-copy sharing: Delta tables ingested, governed and streamed live from local S3-compatible storage into cloud consumers such as Databricks. Neither the server nor the protocol is an atlas entry; the edges are to data federation, the concern zero-copy sharing answers, and to object storage, where the tables sit, and the abstract names no SAP product. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Philipp Nell, written here from SAP's abstract; the recording is not yet published.
HANA Database Migration: Handling Incompatible Changes to Existing TablesHANA Database Migration: Handling Incompatible Changes to Existing TablesThe question schema evolution exists for, asked plainly: how do you restructure a table in a production system that already holds live data. Incompatible changes are the ones CAP's own alter path will not make, which is where this starts.Sekar Somasundaram, published 2025-04-16
SAP Developer New, July 3rd 2026SAP Developer New, July 3rd 2026A "Did You Know" segment in this SAP Developer News video walks through schema evolution: CAP's ability to add a new field to an entity, or make a compatible change to an existing one, then redeploy the model with no data loss or manual migration. The rest of the July 2026 episode covers that month's Developer Challenge, a SAP HANA Cloud Q2 release announcement and a UI5 survey call, none explained in substance here.published 2026-07-02
Building an SAP BTP Agent Architecture from Scratch: Python + CAP + HANABuilding an SAP BTP Agent Architecture from Scratch: Python + CAP + HANAA first-person build log of a Flask orchestrator on Cloud Foundry that reduces a question to keywords, searches a Node.js service's Documents entity, and passes what it finds to Claude for a grounded answer. Getting there means learning that HANA's fuzzy .search() matches one word but not a full sentence, fixed by splitting the query into terms and merging the per-term hits, and that provisioning SAP HANA Cloud hits a database-level free-tier quota rather than an HDI-container one, with a stopped instance needing to be resumed first. It also covers @sap/cds-dk needing to sit in dependencies rather than devDependencies, since Cloud Foundry's buildpack skips the latter, before cds deploy --to hana can run as part of the push.neilaspin, published 2026-07-28
Semantic search in CAP (Node.js): vector embeddings and cosine similaritySemantic search in CAP (Node.js): vector embeddings and cosine similarityFinding the best semantic match for a prompt inside an entity, using local vector embeddings and cosine similarity — and the finding the author leads with is that it works without a vector database at all. Reported as experiments rather than as a pattern, which is the honest register for it: the interesting claim is how little infrastructure the simple case needs.published 2025-12-09
Understanding Fuzzy Search in SAP Fiori ApplicationsUnderstanding Fuzzy Search in SAP Fiori ApplicationsExplains SAP HANA Enterprise Search's fuzzy, relevance-ranked matching behind Fiori's global search bar, its exact-match Search Query Syntax operators, and how a CAP CDS project on @sap/cds tunes the gap between them with @cds.search and @Search.fuzzinessThreshold, shown on a Contracts entity's contractNumber field. Raising the threshold to 0.95 narrows that field to near-exact matches for structured identifiers such as contract numbers, while an unset field keeps HANA's default (~80%) fuzziness for broader free-text discovery.Ruchi5, published 2026-07-27