SAP Datasphere Integration Patterns: Lessons Learned from Two Years of Implementations
Two years of production SAP DatasphereSAP DatasphereSAP's cloud data warehouse: spaces, modelled views and analytic models over data brought in or federated from source systems, with the business context carried along rather than rebuilt.sap official, btp integrations across SAP and non-SAP sources, settling on Replication Flows over remote access for high-volume Finance analytics because remote queries added latency at query time, then tuning the copy with Datasphere-side partitioning, source-side CDS view optimisation and Cloud ConnectorCloud ConnectorSAP's on-premises agent that links SAP BTP applications to systems in a customer's own network, as a reverse invoke proxy that exposes only the systems and resources it is configured to allow.sap official, btp sizing. For file-based and Kafka sources, SAP Integration SuiteSAP Integration SuiteSAP's integration service on BTP: Cloud Integration for orchestration, API Management in front of it, and an MCP gateway that serves a managed API to agents.sap official, btp iFlows did work a direct connection could not — flattening nested JSON, PGP decryption and orchestrating the SAP Ariba extraction built on SAP's own BTP Procurement Data Extractor content.
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- explains → applies_to on capability:warehouse-loadingDoor scope derived from the artifacts this piece also explains, so a door page lists it only where it holds (docs/concepts/content-on-doors.md).
- Entered the atlasDiscovered via SAP Community · cloud-integration-tag.
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