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Databricks releases, every cloud

38 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. Session restore for serverless jobs is in Public Preview

    Restores Python variables and Spark session into a new notebook for debugging or exploration, requires eligible serverless compute job runs.

  3. Manage project environments with %uv commands

    Requires environment version 5 or above. Supports serverless notebooks.

  4. Session restore for serverless jobs is now in Beta

    Restores Python variables and Spark session into a new notebook. Captures state snapshots on failure or long runs.

  5. Search and replace text across files

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

  6. Environment variables for serverless jobs are in Beta

    Requires workspace admin to enable from Previews page.

  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. Organize your work with spaces

    Preserves open tabs for specific folders or projects.

  9. Git CLI commands in Git folders are now in Public Preview

    Enables standard Git commands like git stash and rebase in Databricks terminals. Requires workspace eligibility.

  10. Mention Genie Code in notebook comments

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

  11. Scala and Java UDFs in Unity Catalog are now generally available

    Reuses existing JVM logic, offers better performance than Python UDFs.

  12. Object metadata column is now in Public Preview

    Exposes object properties like MIME type and tags, available in Databricks Runtime 18.1.

  13. MySQL integrated CDC pipeline is now in Beta

    Replaces separate ingestion gateway, requires single pipeline update.

  14. Parquet v2 for Delta Lake tables is generally available

    Requires Databricks Runtime 18.1 and above, set delta.parquet.format.version to 2.12.0.

  15. AUTO CDC flows for streaming tables in Databricks SQL are generally available

    Automatically handles out-of-order records as SCD type 1 or 2, replacing complex MERGE INTO logic.

  16. Auto time-to-live for automatic row deletion is generally available

    Deletes rows from Delta Lake, Iceberg, and streaming tables based on a DATE or TIMESTAMP column.

  17. Converting a partitioned table to liquid clustering is generally available

    Uses ALTER TABLE command, requires Databricks Runtime 18.1 or above.

  18. Lakehouse Replay (Beta)

    Automatically replays serverless workloads against upcoming runtime releases. Requires no setup.

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

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

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

  22. Spark Declarative Pipelines on Lakeflow updates are retained for 60 days

    Retention period increased from 30 to 60 days, applying to UI and REST API updates.

  23. SQL alert task for jobs (Beta)

    Evaluates SQL alerts as part of workflows, enabling automated condition checks and notifications.

  24. Notebook tagging (Public Preview)

    Organizes notebooks for easier management, supports governed tags for trust levels or lifecycle status.

  25. Paste images into notebooks

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

  26. View and restore your recent workspace tab sessions

    Restores up to 10 recent sessions.

  27. View latest scheduled notebook job results

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

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

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

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

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

  30. Databricks Assistant Agent mode: Data Science Agent is in Beta

    Orchestrates multi-step workflows from a single prompt, building entire notebooks for tasks like EDA and machine learning.

  31. Admins can now manage a workspace's serverless base environments (Public Preview)

    Defines custom environment specs for serverless notebooks, allows setting a default for new notebooks.

  32. 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.

  33. Enhanced autocomplete for complex data types in notebooks

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

  34. Serverless compute runtime updated to 17.1

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

  35. Databricks Assistant: User and workspace instructions now available

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

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

    Performs reasoning and editing across multiple cells without manual intervention.

  37. Serverless compute runtime updated to 17.0

    corresponds to Databricks Runtime 17.0, see release notes for details

  38. Improvements to the notebook editing experience

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

  39. Serverless notebooks: Restore Python variables after idle termination

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

  40. 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.