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Databricks releases, every cloud

194 releases of 1357

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  1. Select tables and create pivot tables in Google Sheets

    Imports data via Databricks Connector, selecting from Catalog Explorer.

  2. New GCP regions support serverless compute

    Available in me-central1 and southamerica-east1 regions.

    AWS(not on this cloud)Azure(not on this cloud)GCP, read it on their docsSAP(unknown)
  3. Zendesk Support connector (Beta)

    Ingests ticket, help center, and community forum data from Zendesk Support.

  4. Trigger on update for pipelines (GA)

    Refreshes pipeline when source table changes, usable in Databricks SQL pipeline schedules.

  5. View and restore your recent workspace tab sessions

    Restores up to 10 recent sessions.

  6. Google Drive connector (Beta)

    Supports read_files, spark.read, COPY INTO, and Auto Loader for ingesting files.

  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. You can now use custom base environments for Python, Python Wheels, and notebook tasks in serverless jobs

    Defined with YAML files, they support Python, Python wheel, and notebook tasks.

  9. Ingest Salesforce formula fields incrementally (Beta)

    Replaces snapshotting with incremental ingestion, improving performance and reducing costs.

  10. Row filtering for managed ingestion connectors (Beta)

    Applies conditions like a SQL WHERE clause, available for Google Analytics, Salesforce, and ServiceNow connectors.

  11. Meta Ads connector (Beta)

    Ingests data from Meta Ads, requires setup as a data source.

  12. Login required to download ODBC driver

    Requires login and license acceptance, except for AWS GovCloud which needs account team access.

  13. Serverless compute is now available in Azure China North 3

    Available for notebooks, jobs, pipelines, and SQL warehouses.

    AWS(not on this cloud)Azure, read it on their docsGCP(not on this cloud)SAP(unknown)
  14. Confluence connector (Beta)

    Ingests Confluence spaces and pages into Databricks, requires OAuth U2M configuration.

  15. Serverless workspaces are now available in new GCP regions

    Available in most GCP regions, see documentation for list.

    AWS(not on this cloud)Azure(not on this cloud)GCP, read it on their docsSAP(unknown)
  16. Change owner for materialized views or streaming tables defined in Databricks SQL

    Done through Catalog Explorer, replacing previous methods.

  17. Customizable SharePoint connector (Beta)

    Ingests structured, semi-structured, and unstructured files into Delta tables with customizable schema inference and parsing options.

  18. Discover files in Auto Loader efficiently using file events

    Requires file events enabled on external locations. Replaces directory listing for efficiency.

  19. Jira connector (Beta)

    Ingests Jira issues, comments, and attachments metadata into Databricks.

  20. Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
  21. Configure full refresh behavior for managed database connectors

    Applies to Lakeflow Connect managed database connectors, allowing scheduled full refresh snapshots and automatic recovery from unsupported schema changes.

  22. Serverless compute is now available in new regions

    Added to Australia Southeast, Canada Central, Mexico Central, Norway East, and South Africa North regions.

    AWS(not on this cloud)Azure, read it on their docsGCP(not on this cloud)SAP(unknown)
  23. Databricks SQL version 2025.35 is rolling out in Current

    Includes new features, see documentation for details.

  24. Jobs can now be triggered on source view update

    Supports views referencing supported table types, see documentation for specifics.

  25. Improved full refresh flow for managed database connectors

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

  26. Lakeflow Declarative Pipelines has been renamed to Lakeflow Spark Declarative Pipelines

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

  27. SQL Editor visualization fix

    Tooltips now display in front of the legend.

  28. Serverless notebook tasks can now use jobs environment

    Replaces inherited serverless environment with configurable job environment.

  29. JAR tasks are now supported on serverless compute

    Run JAR jobs without a cluster.

  30. Salesforce ingestion connector supports history tracking (SCD type 2)

    Enables history tracking, overwriting default SCD type 1 behavior.

  31. Databricks SQL version 2025.35 is now available in Preview

    Adds EXECUTE IMMEDIATE constant expressions and LIMIT ALL for recursive CTEs.

  32. Serverless compute has been updated to version 17.3

    Updated from version 17.2, requires no configuration changes.

  33. New alert editing experience

    Replaces old editor with a multi-tab editor for unified workflow.

  34. Jobs can now be triggered on source table update

    Triggers require Databricks Runtime 7.0 or later.

  35. Create backfill job runs

    Triggers job runs to load past data, useful for repairing processing failures.

  36. The billable usage table now records the performance mode of serverless jobs and pipelines

    Records performance mode in product_features.performance_target column with values PERFORMANCE_OPTIMIZED, STANDARD, or null.

  37. Visualizations fix

    Fixes legend selection for charts with aliased series names in SQL editor and notebooks.

  38. Semantic metadata in metric views

    Requires YAML 1.1 and Databricks Runtime 17.3 or higher.

  39. New requirement to create connections for Salesforce ingestion

    Requires Databricks connected app installed. Applies to new connections only.

  40. Databricks SQL version 2025.30 is now available in Preview

    Adds LIKE operator support for UTF8 collations and ST_ExteriorRing function.

  41. Google Analytics Raw Data connector GA

    Enables ingestion of raw Google Analytics data into Databricks, requires Google Analytics 4 and Google BigQuery setup.

  42. Python custom data sources can be used with Spark Declarative Pipelines on Lakeflow

    Supports Python custom data sources and sinks in pipeline definitions.

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