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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.
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.
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
🔴 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.
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.
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.
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.
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.
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.
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
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
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
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
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.
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 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 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
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
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.
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.
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.
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 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 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
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
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
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.
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
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.
Always in Sync — Field-level and event-driven side effects for reactive UIs in RAPAlways in Sync — Field-level and event-driven side effects for reactive UIs in RAPA Devtoberfest 2026 session on side effects in RAP — the declarations in a behaviour definition that tell a draft UI to reload what a change affected, instead of leaving the user to refresh the browser. Field-level side effects recalculate a total price from a determination when a booking fee is entered, including across the association from a child item up to the root entity, and a permissions side effect toggles a description field between read-only and editable; a global side effect is attached to a determine action, fires when the user presses Enter, and only one may exist per business object, which is why the prepare action and a second determine action cannot both carry it. The last part starts a long-running calculation through the background processing framework and raises a business event that the behaviour definition lists as a side effect source and the projection makes public, so the Fiori app is updated with a notification when the work finishes, whether it was triggered by the user or by an application job — the transactional model and the async processing side the edges rest on.published 2026-10-05
Explore SAP Fiori elements for ABAP developersExplore SAP Fiori elements for ABAP developersSAP Fiori elements for an ABAP developer who now builds the UI as well as the RAP business object behind it, the transactional model of ABAP Cloud, in SAP Business Application Studio; the abstract calls the UI side new territory for that developer, and a Fiori elements app is rendered from the service's Fiori annotations rather than hand-written UI code. The abstract names the tool and the stack and does not say which floorplan or annotations are shown. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Björn Schulz, written here from SAP's abstract; the recording is not yet published.
Level up app development: ABAP Cloud model innovations and Joule solutionLevel up app development: ABAP Cloud model innovations and Joule solutionThe ABAP RESTful application programming model, in SAP's abstract, generates multi-node business objects and adds event-driven side effects, collaborative draft, background processing and analytical tables, with the SAP Joule for Developers, ABAP AI capabilities add-on used to speed development up. The generated business objects are the transactional model concern; the abstract names each feature and says nothing about how it is used. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Anne Keller, Carine Tchoutouo Djomo, Frank Jentsch and Marina Blank, written here from SAP's abstract; the recording is not yet published.
What's new with draft handling in RAP?What's new with draft handling in RAP?An ABAP-day session at Devtoberfest 2026 on two additions to draft handling in RAP: collaborative draft, where two users work on the same draft instance and a field is locked only while the other is in it, and draft scope, where editing an instance of one draft-enabled business object puts the related instances of a dependent one into draft as well. Andre Fischer shows what each costs in the behaviour definition and projection, the draft query view and its DCL that collaborative draft needs over a table-based business object, and the CDS table entities that remove both the draft query view and the persistence table, with their current restrictions in ABAP analytics and extensibility; the from-scratch generator in ADT grows a checkbox for them. Both demos run against the DMO flight scenario of SAP-samples/abap-platform-refscen-flight, and the last part hides the draft-related features of an OData V4 app in its manifest, which the session gives as the reason a simple create-update-delete app no longer needs a V2 service binding.published 2026-09-21