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Releases

Week of November 10, 2025

11 releases between November 10, 2025 and November 16, 2025.

Preview
6
Update
5
On
AWS 10, Azure 10, GCP 10
  1. Connect Genie Agents to Microsoft Copilot Studio (Public Preview)

    Requires Managed MCP Servers preview enabled.

  2. Databricks SQL alerts are now in Public Preview

    Offers a new editing experience, replacing the previous version.

  3. Improved full refresh flow for managed database connectors

    Reduces downtime by delaying table refresh until snapshot completion, minimizing PENDING_RESET errors.

  4. OpenAI GPT-5.1 now available as a Databricks-hosted model

    Accessible via Foundation Model APIs and AI Functions for pay-per-token and batch inference workloads.

    AWS, read it on their docsAzure(not on this cloud)GCP, read it on their docsSAP(unknown)
  5. Convert foreign tables to Unity Catalog managed or external tables (Public Preview)

    Requires Databricks Runtime 17.0 LTS or above. Uses ALTER TABLE SET MANAGED or SET EXTERNAL.

  6. Dashboard search and embedding enhancements

    Search now covers widget titles and descriptions, and dataset queries are searchable from the workspace bar.

  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. Genie navigation and accuracy improvements

    Fixes back button error and broken entity matching link. Optimizes column selection for relevance.

  9. JDBC Unity Catalog connection in Beta

    Requires Databricks Runtime 17.3 or above. Available on standard, dedicated, or serverless compute.

  10. SFTP connector (Public Preview)

    Extends Auto Loader to ingest files from SFTP servers.

  11. TISAX compliance controls (Public Preview)

    Enhances workspace compliance based on ISO/IEC 27001 and VDA ISA requirements.

    AWS(not on this cloud)Azure, read it on their docsGCP(not on this cloud)SAP(unknown)
  12. Lakeflow Declarative Pipelines has been renamed to Lakeflow Spark Declarative Pipelines

    Replaces Lakeflow Declarative Pipelines, see Spark Declarative Pipelines for details.

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