Skip to content

Databricks releases, every cloud

24 releases of 1321

Last updated

  1. Base environments are now supported on classic compute (Beta)

    Manages Python dependencies using Databricks-provided or custom environments.

  2. Automatic change data feed will soon be available in all supported regions Coming soon

    Requires Databricks Runtime 19 or above with row tracking enabled. Replaces manual change data feed setup on tables.

  3. Manage project environments with %uv commands

    Requires environment version 5 or above. Supports serverless notebooks.

  4. Search and replace text across files

    Works in Databricks Git folders or Declarative Automation Bundles projects from the Search pane.

  5. Organize your work with spaces

    Preserves open tabs for specific folders or projects.

  6. Mention Genie Code in notebook comments

    Triggers AI help inline by typing @ and selecting Genie Code.

  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. Automatic upgrades will roll out more features to existing tables Coming soon

    Adds row tracking and Checkpoint V2 to existing tables.

  9. Faster package installs with %uv pip in serverless notebooks

    Requires environment version 5 or above. Replaces %pip for faster installs.

  10. Native data profiling for notebook results tables

    View column statistics by selecting headers and clicking Open selection details. Available in notebooks and new SQL editor.

  11. Paste images into notebooks

    Copies images from local file system using ⌘ + V or Ctrl + V.

  12. View and restore your recent workspace tab sessions

    Restores up to 10 recent sessions.

  13. View latest scheduled notebook job results

    Shows latest scheduled run in notebooks and dashboards, can update notebook with latest results.

  14. Real-time collaboration in notebook cells, files, and SQL editor

    Multiple users can edit the same cell simultaneously, viewing each other's edits.

  15. Use Git CLI commands in Git folders (Beta)

    Runs standard Git commands in Databricks web terminal. Requires Git folder setup.

  16. Zstd is now the default compression for new managed tables

    Replaces Snappy compression, applies to Databricks Runtime 16.0 and above.

  17. Track and navigate notebook runs with the new cell execution minimap

    Appears in the right margin, shows cell execution states, and allows clicking to jump to a cell.

  18. Enhanced autocomplete for complex data types in notebooks

    Supports structs, maps, and arrays in SQL cells, and provides column recommendations for CTEs using SELECT *.

  19. Serverless compute runtime updated to 17.1

    corresponds to Databricks Runtime 17.1, see release notes for details.

  20. Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
  21. Databricks Assistant: User and workspace instructions now available

    Custom instructions can be added by users or admins, applying to all Assistant experiences.

  22. Edit mode in Assistant does multi-cell code refactoring and more

    Performs reasoning and editing across multiple cells without manual intervention.

  23. Serverless compute runtime updated to 17.0

    corresponds to Databricks Runtime 17.0, see release notes for details

  24. Improvements to the notebook editing experience

    Adds split view and native find-and-replace tool.

  25. Serverless notebooks: Restore Python variables after idle termination

    Restores Python variables from snapshot after idle termination. Requires reconnection to restore.

  26. Serverless compute is now available in northamerica-northeast1, europe-west1, and asia-northeast1

    Supports notebooks, workflows, and Lakeflow pipelines.

    AWS(not on this cloud)Azure(not on this cloud)GCP, read it on their docsSAP(unknown)

Headlines, dates and product areas are Databricks' own, from the release notes published for each cloud, and every item links to the note it came from. The one-line summaries are ours. Not a Databricks product and not affiliated with Databricks, Inc.