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Databricks releases, every cloud

20 releases of 1321

Last updated

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

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

  2. Environment version 6 is now available

    Supports serverless and standard classic compute.

  3. JAR tasks on serverless compute are now generally available

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

  4. 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.

  5. Automated setup for S3 external locations

    Uses AWS IAM temporary delegation to configure external locations and provision required resources.

    AWS, read it on their docsAzure(not on this cloud)GCP(not on this cloud)SAP, read it on their docs
  6. Agentic code converter is in Beta

    Converts T-SQL, Snowflake, and other dialects to ANSI SQL. Requires workspace admin enablement.

  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. July 6, 2026

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

  9. Workspace admin setting for serverless notebook execution timeout

    Replaces manual override process, defaults to 2.5 hours.

  10. Version 18.2

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

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

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

  12. 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.

  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. Serverless workspaces are now generally available

    Come pre-configured with serverless compute and default storage.

  17. 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.

  18. Serverless notebook tasks can now use jobs environment

    Replaces inherited serverless environment with configurable job environment.

  19. Serverless compute has been updated to version 17.3

    Updated from version 17.2, requires no configuration changes.

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  21. 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.

  22. 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.

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.