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Databricks releases, every cloud

33 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. Git Folder Serverless is in Beta

    Shares serverless compute and pyproject.toml environment across notebooks and files.

  5. 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.

  6. Write data back to Databricks from Google Sheets

    Creates or overwrites Unity Catalog tables from Google Sheets.

    AWS, read it on their docsAzure(not on this cloud)GCP, read it on their docsSAP(unknown)
  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. Manage project environments with %uv commands

    Requires environment version 5 or above. Supports serverless notebooks.

  9. JAR tasks on serverless compute are now generally available

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

  10. Filter updates for the Databricks Excel Add-in

    Supports cascading filters and case-insensitive string matching, replaces LIKE and IN filters.

    AWS, read it on their docsAzure(not on this cloud)GCP, read it on their docsSAP(unknown)
  11. 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.

  12. Web terminal on serverless GPU compute (AI Runtime) is in Public Preview

    Runs shell commands, monitors GPU usage, and manages files on serverless GPU compute. Requires environment version 5 or above.

    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(unknown)
  13. Dedicated group clusters will soon be available by default for workspaces with the compliance security profile enabled Coming soon

    Enables shared compute for groups with compliance security profile, supporting Databricks Runtime for ML and RDD APIs.

  14. July 6, 2026

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

  15. Schedule deferred policy enforcement for all-purpose compute

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

  16. Workspace admin setting for serverless notebook execution timeout

    Replaces manual override process, defaults to 2.5 hours.

  17. Instance events and instance pools system tables are now available (Public Preview)

    Track instance state transitions and instance pool configurations via system.compute.instance_events and system.compute.instance_pools tables.

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

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

  19. Version 18.2

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

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

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

  22. 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.

  23. Version 18.1

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

  24. Compute log delivery to volumes is now GA

    Delivers Spark driver, worker, and event logs to Unity Catalog volumes, recommended for log storage.

  25. Version 18.0

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

  26. Serverless environment version 5 is now available

    Includes CPU and GPU versions.

  27. Serverless workspaces are now generally available

    Come pre-configured with serverless compute and default storage.

  28. 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.

  29. Flexible node types are now generally available

    Falls back to alternative instance types when specified type is unavailable, improving launch reliability.

  30. JDBC Unity Catalog connection in Beta

    Requires Databricks Runtime 17.3 or above. Available on standard, dedicated, or serverless compute.

  31. Serverless notebook tasks can now use jobs environment

    Replaces inherited serverless environment with configurable job environment.

  32. Serverless compute has been updated to version 17.3

    Updated from version 17.2, requires no configuration changes.

  33. 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)
  34. 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.

  35. 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.