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Databricks releases, every cloud

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

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

  3. Environment version 6 is now available

    Supports serverless and standard classic compute.

  4. Default Python package repositories are GA for Lakeflow pipelines and classic compute

    Supports private or authenticated registries as workspace defaults. Applies to UI and API created classic compute.

  5. Manage project environments with %uv commands

    Requires environment version 5 or above. Supports serverless notebooks.

  6. July 6, 2026

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

  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. Schedule deferred policy enforcement for all-purpose compute

    Applies on next restart or immediately, and admins can cancel scheduled enforcements.

  9. Workspace admin setting for serverless notebook execution timeout

    Replaces manual override process, defaults to 2.5 hours.

  10. Databricks Container Services for standard compute is now available (Beta)

    Requires Databricks Runtime 18.3 or later, allows custom Docker images in shared compute.

  11. Version 18.2

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

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

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

  13. Version 18.1

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

  14. Version 18.0

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

  15. Serverless environment version 5 is now available

    Includes CPU and GPU versions.

  16. Change to use_case field in VPC endpoint API responses Coming soon

    Changes from WORKSPACE_ACCESS to GENERAL_ACCESS, see API docs for details.

    AWS, read it on their docsAzure(not on this cloud)GCP, read it on their docsSAP(unknown)
  17. 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)
  18. 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.

  19. 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)
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  21. Serverless notebook tasks can now use jobs environment

    Replaces inherited serverless environment with configurable job environment.

  22. Serverless compute has been updated to version 17.3

    Updated from version 17.2, requires no configuration changes.

  23. Configure compute to use AWS Capacity Blocks

    Replaces on-demand instances, requires AWS account setup.

    AWS, read it on their docsAzure(not on this cloud)GCP(not on this cloud)SAP(unknown)
  24. 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.

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.