Concept card

BDC Connect for Databricks

As of 2026-07-24T14:00:00Z

Edited by Cédric-Olivier Mâry, sole editor and publication director — 27 years in the SAP ecosystem. How these pages are produced, and where automation is used.

What is BDC Connect for Databricks?

BDC Connect for Databricks, GA on 2025-10-06, is a true zero-copy bidirectional bridge via Delta Sharing — a Databricks Delta table becomes a queryable BDC Data Product and vice versa, with no ETL pipeline and no data leaving its authoritative store.

How does SAP business data cloud work with Databricks?

Short answer above

BDC Connect for Databricks is the zero-copy bridge that lets SAP Business Data Cloud and a Databricks Lakehouse read each other's governed data without either side copying, exporting, or replicating a single row. For any architect weighing a Databricks-heavy analytics estate against SAP's own semantic layer, it changes the question from "which platform wins" to "how do the two platforms share one governed truth."

What it is and why it matters

Historically, connecting SAP data to a Databricks Lakehouse — or vice versa — meant building and maintaining an extract-transform-load pipeline: a batch job, a staging area, a second copy of the data that could drift out of sync with the source and that needed its own access controls, its own monitoring, its own failure recovery. BDC Connect for Databricks removes that pipeline entirely by using the Delta Sharing open protocol, the same mechanism Databricks already uses to share Delta Lake tables across organisational boundaries, paired with SAP's own data product governance layer inside BDC. The result is not a connector in the traditional sense; it is a shared governance contract laid over two separate storage planes that never actually move data between them.

How it works

Why it matters

The direct SQL query example is concrete proof the integration is genuinely zero-copy, not a marketing claim — reads go straight from BDC-managed storage to the Databricks compute cluster.
OAuth 2.0 bearer-token registration per BDC tenant is the actual security mechanism — a specific detail worth verifying against a client's IAM model before scoping.
Governance (owner, freshness SLA, classification) applies to every Data Product published either direction — this is a governed marketplace, not a raw data pipe.

Key points

BDC Connect for Databricks is mastered only when it changes a named buyer decision.
Start with the semantic contract and control model before demonstrating the tool.
Use current SAP, analyst, study, KG, and news signals as evidence, not decoration.
Separate verified facts from directional trends and modeled assumptions.
Define owner, metric, threshold, support path, and rollback before scaling.
For non-AI use cases, still define quality, adoption, and operating ownership.
Leave a reusable operating asset: memo, checklist, control table, and exception log.
A premium answer is short, trade-off explicit, and defensible in a steering committee.

Terms used on this page

Decision owner: The accountable person who accepts the trade-off and funds the next action.
Semantic contract: The shared definition of business terms, metrics, entities, and access rules used by tools and teams.
Control plane: The layer that applies policy, access, lineage, monitoring, and escalation across the operating model.
Evidence grade: A label that separates verified fact, directional signal, modeled assumption, and field observation.
Adoption metric: The measurable behavior proving that the concept changed actual work after go-live.
Reusable IP: An artifact, checklist, or model that can be reused across clients without copying client-specific data.
Decision owner: The accountable person who accepts the trade-off and funds the next action.
Semantic contract: The shared definition of business terms, metrics, entities, and access rules used by tools and teams.

Sources

Full card available to members. What the full card adds: the full decision framework · the SAP vs Snowflake / Databricks / Fabric comparison · the common pitfalls and their fix · the cheat sheet · the architecture schemas · the code blocks · the facts worth quoting.

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