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Databricks releases, every cloud

60 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. Standard performance mode is now available for one-time runs in the Jobs API

    Sets performance_target to STANDARD. Supports Apache Airflow's DatabricksSubmitRunOperator.

  4. Environment version 6 is now available

    Supports serverless and standard classic compute.

  5. Manage project environments with %uv commands

    Requires environment version 5 or above. Supports serverless notebooks.

  6. 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.

  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. JAR tasks on serverless compute are now generally available

    Requires matching Scala, Java Development Kit, and Databricks Connect versions.

  9. Search and replace text across files

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

  10. Environment variables for serverless jobs are in Beta

    Requires workspace admin to enable from Previews page.

  11. Organize your work with spaces

    Preserves open tabs for specific folders or projects.

  12. Serverless compute access control is now generally available

    Governs access to notebooks, jobs, and pipelines through Default Interactive and Automated Compute objects. Existing workloads run unchanged.

  13. 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.

  14. Mention Genie Code in notebook comments

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

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

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

  16. Object metadata column is now in Public Preview

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

  17. July 6, 2026

    Updates from Databricks Runtime 18, adds Spark Declarative Pipelines and IP address functions.

  18. MySQL integrated CDC pipeline is now in Beta

    Replaces separate ingestion gateway, requires single pipeline update.

  19. 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.

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

  22. 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.

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

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

  24. Lakehouse Replay (Beta)

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

  25. Workspace admin setting for serverless notebook execution timeout

    Replaces manual override process, defaults to 2.5 hours.

  26. Version 18.2

    Adds CREATE OR REPLACE TEMP TABLE syntax and upgrades Snowflake JDBC driver to 3.28.0.

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

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

  28. 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.

  29. 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.

  30. Workspace base environments are now generally available

    Lets workspace admins create pre-built environments for serverless notebooks, enabled by default in compliance security profile workspaces.

  31. Version 18.1

    Supports DATETIMEOFFSET for Azure Synapse and adds schema evolution with INSERT statements.

  32. SQL alert task for jobs (Beta)

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

  33. Serverless compute now available for IRAP and Canada Protected B workloads on Azure Databricks

    Requires environment version 5 to be enabled.

    AWS(not on this cloud)Azure, read it on their docsGCP(not on this cloud)SAP(not on this cloud)
  34. Notebook tagging (Public Preview)

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

  35. Version 18.0

    Upgrades Redshift JDBC driver to 2.1.0.28, adds SQL window functions to metric views.

  36. Serverless environment version 5 is now available

    Includes CPU and GPU versions.

  37. Serverless compute now available for compliance standards

    Adds HITRUST, PCI-DSS, TISAX, and UK Cyber Essentials Plus support.

    AWS(not on this cloud)Azure, read it on their docsGCP(not on this cloud)SAP(unknown)
  38. 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)
  39. Paste images into notebooks

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

  40. View and restore your recent workspace tab sessions

    Restores up to 10 recent sessions.

  41. Serverless workspaces are now generally available

    Come pre-configured with serverless compute and default storage.

  42. 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.

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.