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Databricks releases, every cloud

41 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. Organize your work with spaces

    Preserves open tabs for specific folders or projects.

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

  9. Mention Genie Code in notebook comments

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

  10. Managed Iceberg materialized views are in Public Preview

    Requires account team enablement. Compatible with external Iceberg readers.

  11. Genie Code now supports auto-approve for tool actions

    Approves tool actions without prompts, using an AI classifier to block risky ones.

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

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

  13. 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.

  14. Sample Data Explorer is generally available

    Lets you ask questions about Unity Catalog tables using natural language, returning SQL queries.

  15. Workspace skills for Genie Code are now available

    Workspace admins can create shared skills for machine learning pipelines and domain-specific processes.

  16. Databricks Assistant is now Genie Code

    Adds autonomous multi-step data tasks, replaces Databricks Assistant.

  17. Notebook tagging (Public Preview)

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

  18. Connect Databricks Assistant to MCP servers

    Connects to external tools and data sources through MCP servers, requiring permission to use added servers.

  19. Partner-powered AI features are now supported in the Canada, Brazil, and United Kingdom Azure Geographies

    Uses models hosted in the same Azure Geography as the workspace, requires cross-geo processing for some features.

    AWS(not on this cloud)Azure, read it on their docsGCP(not on this cloud)SAP(unknown)
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  21. Paste images into notebooks

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

  22. View and restore your recent workspace tab sessions

    Restores up to 10 recent sessions.

  23. Create skills for Databricks Assistant

    Extends Databricks Assistant with domain-specific tasks, following the open Agent Skills standard.

  24. Databricks Assistant Agent mode is now in Public Preview

    Automates multiple steps from a single prompt, using Azure OpenAI or Anthropic.

  25. View latest scheduled notebook job results

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

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

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

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

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

  28. Databricks Assistant Agent mode can now use models served through Anthropic on Databricks

    Requires partner-powered AI features to be enabled. Uses endpoints hosted by Databricks.

    AWS(not on this cloud)Azure, read it on their docsGCP(not on this cloud)SAP(unknown)
  29. The Data Science Agent can now also use models served through Anthropic on Databricks

    Uses models served through Anthropic when partner-powered AI features are enabled. Requires partner-powered AI features to be enabled.

    AWS, read it on their docsAzure(not on this cloud)GCP, read it on their docsSAP(unknown)
  30. Notebook improvements

    Cell execution minimap appears in right margin, supports up to 100MB notebooks.

  31. 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.

  32. 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.

  33. 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.

  34. Enhanced autocomplete for complex data types in notebooks

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

  35. Databricks Assistant integrated with compute

    Creates compute resources, pools, and policies, and answers questions about them. Available on some compute pages.

  36. Serverless compute runtime updated to 17.1

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

  37. Databricks-hosted models for Assistant are now GA

    Available on all cloud platforms at no extra cost.

  38. Databricks Assistant: User and workspace instructions now available

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

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

    Performs reasoning and editing across multiple cells without manual intervention.

  40. Serverless compute runtime updated to 17.0

    corresponds to Databricks Runtime 17.0, see release notes for details

  41. Improvements to the notebook editing experience

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

  42. Serverless notebooks: Restore Python variables after idle termination

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

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.