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Databricks releases, every cloud

229 releases of 1321

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  1. The update_flow API for Spark Declarative Pipelines on Lakeflow is generally available

    Writes to a sink in update output mode, emitting only changed rows. Supports stateful aggregations without a watermark.

  2. Aha! connector (Beta)

    Ingests data from Aha!, using Lakeflow Connect.

  3. Monday.com managed ingestion connector (Beta)

    Ingests boards, users, teams, and activity logs from Monday.com into Databricks.

  4. Zoho Books managed ingestion connector (Beta)

    Ingests invoices, bills, contacts, and bank transactions from Zoho Books into Databricks.

  5. External data access for pipeline streaming tables and materialized views (Public Preview)

    Enables external Delta and Iceberg clients to read data without copying. Uses Unity Catalog and Iceberg catalog REST APIs.

  6. Managed SharePoint connector adds structured file ingestion and file metadata support (Beta)

    Supports CSV, JSON, XML, Excel, Parquet, Avro, ORC ingestion, replacing unstructured-only approach.

  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. UNIQUE constraint support is now in Public Preview

    Enables join elimination and DISTINCT simplification on Photon-enabled compute. Applies to Unity Catalog Delta Lake tables.

  9. Table update triggers on Delta Sharing and system tables (Beta)

    Monitors data shared through Delta Sharing and system tables, triggering jobs on updates, supporting Databricks-to-Databricks sharing only.

  10. Managed RabbitMQ connector (Beta)

    Streams messages from RabbitMQ classic queues into Unity Catalog streaming tables.

  11. Pendo connector (Beta)

    Ingests data from Pendo into Lakeflow. Requires Lakeflow Connect.

  12. Query-based connectors for Lakeflow Connect are now generally available

    Ingests data from databases like Oracle and PostgreSQL without CDC configuration.

  13. Google Drive managed ingestion connector (Beta)

    Ingests files from Google Drive into Databricks, supporting unstructured and structured data.

  14. Real-time mode in Spark Declarative Pipelines on Lakeflow, and the update_flow API are now available (Public Preview)

    Achieves end-to-end latency as low as 5ms, uses update output mode.

  15. Refresh policies and EXPLAIN CREATE MATERIALIZED VIEW for materialized views are now generally available

    Requires Databricks Runtime 17.3 and above. Available in Databricks SQL.

  16. Databricks SQL version 2026.15 is now available in Preview

    XPath no longer fetches external DTDs, fixing failures from malformed URLs.

  17. Spark Declarative Pipelines on Lakeflow parameters are now in Beta

    Define key-value pairs at pipeline level, referenced in SQL using named parameter syntax.

  18. Fixed LOD expression syntax update for metric views

    Uses SQL window functions, replacing two-step pre-computation approach.

  19. Customer-managed keys now support MLflow managed evaluation features

    Supports MLflow 3 scorers and requires non-CMK encrypted catalog.

  20. Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
  21. Unified runs list is generally available

    Replaces separate job and pipeline run lists, adds filtering and error code visualization.

  22. Spark Declarative Pipelines on Lakeflow sinks are now generally available

    Supports writing to Delta tables, Kafka topics, and Azure Event Hubs.

  23. Databricks SQL alerts are now generally available

    Monitors data and KPIs by running scheduled queries, notifying recipients when conditions are met.

  24. Spark Declarative Pipelines on Lakeflow environment versions (Beta)

    Pins Python version and libraries, decoupling from Databricks Runtime upgrades.

  25. SQL alert task in Lakeflow Jobs is now in Public Preview

    Evaluates a Databricks SQL alert as part of a Lakeflow Job, returning its state as output.

  26. HubSpot connector (GA)

    Ingests data from HubSpot Marketing Hub into Databricks.

  27. Standalone pipelines on serverless general compute (Beta)

    Requires serverless general compute, created via SQL or Python.

  28. GitHub managed ingestion connector (Beta)

    ingests GitHub data into Databricks, available in Lakeflow Connect.

  29. Outlook managed ingestion connector (Beta)

    Ingests email data from Microsoft Outlook into Databricks.

  30. Smartsheet managed ingestion connector (Beta)

    Ingests Smartsheet data into Databricks, available in Lakeflow Connect.

  31. Lakeflow Pipelines Editor is now generally available

    Offers agent-first experience with Genie Code for creating production pipelines.

  32. Community connectors (Beta)

    Extends Lakeflow Connect to unsupported sources, built by the community.

  33. Native data profiling for results tables in the SQL editor

    Select column headers and click Open selection details to view statistics.

  34. agg SQL function as a synonym for measure

    Replaces measure, used as agg(measure_column) in metric views.

  35. Disabling tasks in Lakeflow Jobs is now GA

    Disabled tasks retain config and run history, can be re-enabled later.

  36. MLflow trace storage in Unity Catalog is now in Public Preview

    Stores OpenTelemetry traces, governed by Unity Catalog permissions, queryable from Databricks SQL or MLflow Python SDK.

  37. 5X-Large SQL warehouse size (Public Preview)

    Provides 512 workers, available in all regions, controlled from Previews page.

  38. Zendesk Support connector (GA)

    Allows syncing Zendesk tickets to Databricks.

  39. Confluence connector (GA)

    Allows reading Confluence spaces and pages into Databricks.

  40. Databricks SQL version 2026.10 is rolling out in Current

    Replaces version 2026.09, requires no configuration changes.

  41. Lakeflow Designer is now in Public Preview

    Offers drag-and-drop canvas and natural language for building data workflows.

  42. Query-based connectors for Lakeflow Connect (Public Preview)

    Ingests data from databases using a cursor column, supporting Oracle, Teradata, and others.

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