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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.
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.
Building an Analytical List Page with CAP OData V4Building an Analytical List Page with CAP OData V4The annotations a CAP OData V4 service needs before an Analytical List Page will render — the write-up behind the cap-alp sample indexed here. Candid about its provenance: the author credits a GitHub repository she found the approach in, and notes that the repository is no longer available, which is the whole argument for indexing the reasoning rather than only linking the code.published 2023-06-12
Building an Analytical List Page with CAP OData V4
cap-alp: no published releases, repository quiet for 24 months. Affects A recipe, Runnable code.
Empowering Your Data Analytics with GPT-3 and SAP CAP IntegrationEmpowering Your Data Analytics with GPT-3 and SAP CAP IntegrationFree text in, SQL out, answer back in a sentence — the model writes the query, CAP runs it, and the model turns the rows into prose. Written in the GPT-3 window, so the model access has dated, but the three-step shape has not, and it is a different bet from retrieval: nothing is embedded, the schema is the context.Former Member, published 2023-03-10
Fiori Elements Analytical Table with CAP: Does it work with V2 and V4?Fiori Elements Analytical Table with CAP: Does it work with V2 and V4?A question in the title and an answer in the post, with the boundary drawn carefully: this is an analytical table inside a List Report, not the Analytical List Page, and the two protocol versions do not behave the same.published 2023-04-03
Fiori Elements Analytical Table with CAP: Does it work with V2 and V4?
Fiori annotations changed in @sap/cds-dk 9.6.0, 2025-12-17. Affects Runnable code.
How to transfer file from CAP backsideHow to transfer file from CAP backsideA PDF arriving from the front end, stored against the record with @Core.MediaType, and then sent on to an external service for parsing. Short, and the second half is the part that is not in the plugin documentation: getting the bytes back out of the model to forward them somewhere else.published 2023-09-14
How to transfer file from CAP backside
Attachments has changed 3 times since this was published, most recently in @cap-js/sdm 1.0.0, 2024-06-26. Affects Runnable code.
Presenting sap-cap-sdm-plugin: Effortless Integration Between CAP (Node.js) and DMSPresenting sap-cap-sdm-plugin: Effortless Integration Between CAP (Node.js) and DMSThe author's introduction of the plugin, and unusually clear about its lineage: the idea came from a post about cds.plugins whose example did nothing more than append an emoji to annotated properties, and the groundwork was an earlier library, sap-cloud-cmis-client, that this builds on. Worth reading for how a plugin gets conceived as much as for what it does with Document Management Service.published 2023-10-02
Presenting sap-cap-sdm-plugin: Effortless Integration Between CAP (Node.js) and DMS
sap-cap-sdm-plugin is archived. Its last release was 2024-03-24. Affects Runnable code.
Upload attachments in a Freestyle UI5 and CAP appUpload attachments in a Freestyle UI5 and CAP appAttachments where the UI is freestyle rather than Fiori elements, so none of the generated upload behaviour applies and both ends have to be written.published 2023-12-19
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 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.
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.
[Part – 2] Enrich CAP based Services with Behaviors using Annotations[Part – 2] Enrich CAP based Services with Behaviors using AnnotationsThe second half of a two-part walkthrough of CAP's behavioral annotations, following on from access control and input validation in the first part. This post works through @cds.autoexpose, @cds.api.ignore, @cds.persistence.exists/skip, @cds.on.insert/@cds.on.update and the @odata.Type/@odata.singleton mapping overrides, all shaping how a CDS model is projected into a service, which is data modelling. Alongside these it covers @cds.query.limit for default and maximum page sizes (pagination and streaming), @odata.etag with exclusive and shared locks for optimistic concurrency (concurrency control), and @cds.search for scoping $search to chosen elements (search), each with a CDS code example.published 2023-01-29
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.
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.
[Part – 2] Enrich CAP based Services with Behaviors using Annotations[Part – 2] Enrich CAP based Services with Behaviors using AnnotationsThe second half of a two-part walkthrough of CAP's behavioral annotations, following on from access control and input validation in the first part. This post works through @cds.autoexpose, @cds.api.ignore, @cds.persistence.exists/skip, @cds.on.insert/@cds.on.update and the @odata.Type/@odata.singleton mapping overrides, all shaping how a CDS model is projected into a service, which is data modelling. Alongside these it covers @cds.query.limit for default and maximum page sizes (pagination and streaming), @odata.etag with exclusive and shared locks for optimistic concurrency (concurrency control), and @cds.search for scoping $search to chosen elements (search), each with a CDS code example.published 2023-01-29
#BTP #SAPCAP: Quirky Nuggets (N01-N02)#BTP #SAPCAP: Quirky Nuggets (N01-N02)Walks through two CAP gotchas: the on/before/after phases of custom event handlers, shown with an after handler whose edits only reach the result when the handler returns an object or array, never a primitive; and the @assert.unique annotation, which builds a database uniqueness constraint from the model. For Input validation, the catch is that once the constrained property is nested, @assert.unique must name it by its model dot path (assignment.type) rather than the flattened column data modelling compiles it to (assignment_type).published 2023-06-05
#CAP-TechBytes Input Validation#CAP-TechBytes Input ValidationThe annotations one at a time — @mandatory, @assert.unique, @assert.range including the enum form, @assert.format — each with what it produces. Ends on error handling, which is the part that decides whether any of it is usable from a UI.Thajunniza, published 2023-07-07
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.
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
Use Aspects, Association and Convert OData V4 to V2 using ProxyUse Aspects, Association and Convert OData V4 to V2 using ProxyTwo halves that turn out to belong together: aspects and associations in the model, and then the v4-to-v2 proxy in front of it. The model decides what the proxy has to carry, which is why the author put them in one post.rahul_rajagopal, published 2023-08-28
[BTP HANA Cloud Database] : How to access HANA Cloud Database & HDI Container in BTP[BTP HANA Cloud Database] : How to access HANA Cloud Database & HDI Container in BTPGetting at the database your application already deployed to, which sounds trivial until the HDI container is the only thing that has credentials for it. Guidance for the case where the account is already configured and the question is only how to look inside.showkath_naseem, published 2023-01-18
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.
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.
CAP PostgreSql setup local debugging using Docker - Part 2CAP PostgreSql setup local debugging using Docker - Part 2PostgreSQL in a container so the local loop matches the deployed one — the thing SQLite quietly stops you doing. Short, and it assumes the project from part one already runs.ramonlee5, published 2023-11-22
CAP PostgreSql setup local debugging using Docker - Part 2
Database connectors has changed twice since this was published, most recently in @sap/cds 10.1.0, 2026-09-07. Affects A recipe.
CAP with PostgreSQL DB alternate to HANA Cloud DB - Part 1CAP with PostgreSQL DB alternate to HANA Cloud DB - Part 1Bootstrapping a CAP project on PostgreSQL, framed as a choice that depends on the client rather than on the technology. Short, and part two is where it gets debuggable.ramonlee5, published 2023-10-10
Exposing Calculation View with Dynamic Client via OData APIExposing Calculation View with Dynamic Client via OData APIGetting a HANA Cloud calculation view — built in Business Application Studio and deployed to an HDI container, which is the recommended way to build native HANA artifacts — out through an OData API. The gap it fills is the one between HANA-native development and a service a client can call, which CAP does not cover for artifacts it did not generate.published 2023-10-04
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.
Hybrid testing using PostgreSQL on SAP BTP, hyperscaler optionHybrid testing using PostgreSQL on SAP BTP, hyperscaler optionA short note rather than a guide — the author says they came across the feature reading someone else's post on PostgreSQL with Kyma. Hybrid testing against a real PostgreSQL instance, which until then people assumed meant HANA.martinfrick, published 2023-08-08
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 Deep dive into CAPM and HANA Cloud --> HANACapLets Deep dive into CAPM and HANA Cloud --> HANACapShort, and framed as what the author does day to day on BTP rather than as a tutorial: where CAPM meets HANA Cloud and which pieces have to agree.shivamshukla12, published 2023-07-16
Lets Deep dive into CAPM and HANA Cloud --> HANACap
Database connectors has changed twice since this was published, most recently in @sap/cds 10.1.0, 2026-09-07. Affects Runnable code.
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.
Open Sourcing CAP – how to learn more or get involvedOpen Sourcing CAP – how to learn more or get involvedA roundup of CAP's open-sourcing, begun at TechEd the year before, pointing to a webinar recording, a podcast episode and reCAP 2023 talks for background. Among the components it names are a feature toggle library giving Node.js CAP apps live-updatable toggles backed by Redis, a new pluggable database layer with SQLite and PostgreSQL implementations plus a generic SQL layer, and a change tracking component that builds a change history for data from CDS models.Fempel, published 2023-10-02
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.
Run and Deploy SAP CAP (Java) with PostgreSQL on SAP BTP Cloud FoundryRun and Deploy SAP CAP (Java) with PostgreSQL on SAP BTP Cloud FoundrySuperseded by its own author: the post now opens with a notice that @sap/cds 7.0.0 brought native PostgreSQL support and that @cap-js/postgres should be used instead of the packages described below. Kept because that notice is the record of when the community adapter stopped being the answer.shanthakumar_krishnaswamy, published 2023-04-04
Run and Deploy SAP CAP (Java) with PostgreSQL on SAP BTP Cloud Foundry
cds-pg. Affects Runnable code.
Run and Deploy SAP CAP (Java) with PostgreSQL using Official Database Adapter @cap-js/postgresRun and Deploy SAP CAP (Java) with PostgreSQL using Official Database Adapter @cap-js/postgresThe post that records a handover. The author's earlier writing relied on the community projects cds-pg and cds-dbm; this one states that both were deprecated in favour of the official PostgreSQL support arriving with @sap/cds 7, and rewrites the path around @cap-js/postgres. For CAP Java it takes a different route to the initial schema.sql than the Node.js case, and it is candid that automatic schema deployment is convenient but not always what you want. Dated evidence for why two artifacts here went quiet.shanthakumar_krishnaswamy, published 2023-08-02
Run and Deploy SAP CAP (Java) with PostgreSQL using Official Database Adapter @cap-js/postgres
cds 7, line ended. Affects A recipe, Runnable code.
Run and Deploy SAP CAP (Node.js or Java) with PostgreSQL on SAP BTP Cloud FoundryRun and Deploy SAP CAP (Node.js or Java) with PostgreSQL on SAP BTP Cloud FoundryBoth runtimes in one walkthrough, and it stops on schema evolution — which is the reason to read it rather than one of the several other PostgreSQL posts here, since that is where the PostgreSQL story diverges from HANA's and the deploy stops being automatic.TiaXu, published 2023-07-12
Run and Deploy SAP CAP (Node.js or Java) with PostgreSQL on SAP BTP Cloud Foundry
Database connectors has changed twice since this was published, most recently in @sap/cds 10.1.0, 2026-09-07. Affects A recipe, Runnable code.
SAP CAP (Java) with Amazon Aurora PostgreSQLSAP CAP (Java) with Amazon Aurora PostgreSQLPostgreSQL, but the hyperscaler's own managed global database rather than BTP's option — Aurora, from CAP Java. One of a pair published the same day, the other being Azure's equivalent.shanthakumar_krishnaswamy, published 2023-08-02
SAP CAP (Java) with Amazon Aurora PostgreSQL
Database connectors has changed twice since this was published, most recently in @sap/cds 10.1.0, 2026-09-07. Affects A recipe, Runnable code.
SAP CAP (Java) with Azure Cosmos DB for PostgreSQLSAP CAP (Java) with Azure Cosmos DB for PostgreSQLThe Azure half of the pair: Cosmos DB speaking PostgreSQL, used from CAP Java. Same shape as the Aurora post, and reading both is how you see what is actually portable between them.shanthakumar_krishnaswamy, published 2023-08-02
SAP CAP (Java) with Azure Cosmos DB for PostgreSQL
Database connectors has changed twice since this was published, most recently in @sap/cds 10.1.0, 2026-09-07. Affects A recipe, Runnable code.
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.
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.
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.
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.
Run and Deploy SAP CAP (Java) with PostgreSQL using Official Database Adapter @cap-js/postgresRun and Deploy SAP CAP (Java) with PostgreSQL using Official Database Adapter @cap-js/postgresThe post that records a handover. The author's earlier writing relied on the community projects cds-pg and cds-dbm; this one states that both were deprecated in favour of the official PostgreSQL support arriving with @sap/cds 7, and rewrites the path around @cap-js/postgres. For CAP Java it takes a different route to the initial schema.sql than the Node.js case, and it is candid that automatic schema deployment is convenient but not always what you want. Dated evidence for why two artifacts here went quiet.shanthakumar_krishnaswamy, published 2023-08-02
Run and Deploy SAP CAP (Java) with PostgreSQL using Official Database Adapter @cap-js/postgres
cds 7, line ended. Affects A recipe, Runnable code.
Run and Deploy SAP CAP (Node.js or Java) with PostgreSQL on SAP BTP Cloud FoundryRun and Deploy SAP CAP (Node.js or Java) with PostgreSQL on SAP BTP Cloud FoundryBoth runtimes in one walkthrough, and it stops on schema evolution — which is the reason to read it rather than one of the several other PostgreSQL posts here, since that is where the PostgreSQL story diverges from HANA's and the deploy stops being automatic.TiaXu, published 2023-07-12
Run and Deploy SAP CAP (Node.js or Java) with PostgreSQL on SAP BTP Cloud Foundry
Database connectors has changed twice since this was published, most recently in @sap/cds 10.1.0, 2026-09-07. Affects A recipe, Runnable code.
[Part – 2] Enrich CAP based Services with Behaviors using Annotations[Part – 2] Enrich CAP based Services with Behaviors using AnnotationsThe second half of a two-part walkthrough of CAP's behavioral annotations, following on from access control and input validation in the first part. This post works through @cds.autoexpose, @cds.api.ignore, @cds.persistence.exists/skip, @cds.on.insert/@cds.on.update and the @odata.Type/@odata.singleton mapping overrides, all shaping how a CDS model is projected into a service, which is data modelling. Alongside these it covers @cds.query.limit for default and maximum page sizes (pagination and streaming), @odata.etag with exclusive and shared locks for optimistic concurrency (concurrency control), and @cds.search for scoping $search to chosen elements (search), each with a CDS code example.published 2023-01-29
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.
