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Domain: Data & Persistence
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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
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
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
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
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
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
CAP in the age of AI #6 - vector embeddingsCAP in the age of AI #6 - vector embeddingsVector embeddings put to work in the incident management sample, answering whether this problem has been seen before. An embedding element of type Vector is calculated and stored from the vector_embedding function, so the database refreshes it whenever the text behind it changes, and cosine_similarity compares it with a freshly embedded string; because a title says little, a scheduled action first summarises each incident's conversation through a model on SAP AI Core and the embedding is taken from that summary. The similar-incidents list is a view joining incidents to themselves, with order and limit set in a before handler on the expanded query, and the vector element excluded from the service, since OData knows nothing about vectors — on SAP HANA Cloud the function is native, while SQLite needs packages added to the project.published 2026-10-09
CAP in the age of AI #7 - vector embeddings wrap-upCAP in the age of AI #7 - vector embeddings wrap-upThe same embeddings model taken from SQLite to SAP HANA Cloud, then handed to an agent. Locally it is @cap-js/ai that adds the vector functions SQLite lacks and downloads an all-MiniLM L6v2 ONNX model on first start; on HANA natural language processing has to be switched on, the model name is a mandatory argument, the vectors it returns are 768 dimensions, and dimensions must match on both sides of a comparison. HANA itself can be given SAP AI Core as a remote source for other embedding models, which a CDS.ql expression has to inject because the postfix notation only takes what the CDS model holds, and the hour ends with a search function over cosine similarity exposed over @cap-js/mcp, so an agent asked about low output from solar panels calls semantic search instead of writing the query itself.published 2026-10-16
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 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
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