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Databricks releases, every cloud

38 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. Custom trace views in the MLflow trace explorer are in Beta

    Genie generates views based on plain language descriptions, surfacing relevant trace fields and metrics.

  4. JAR tasks on serverless compute are now generally available

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

  5. 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.

  6. MLflow trace storage in Unity Catalog is now generally available

    Stores traces in OpenTelemetry format with unlimited storage and SQL query access.

  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. Genie Code now supports auto-approve for tool actions

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

  10. Workspace admin setting for serverless notebook execution timeout

    Replaces manual override process, defaults to 2.5 hours.

  11. Customer-managed keys now support MLflow managed evaluation features

    Supports MLflow 3 scorers and requires non-CMK encrypted catalog.

  12. Version 18.2

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

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

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

  14. MLflow trace storage in Unity Catalog is now in Public Preview

    Stores OpenTelemetry traces, governed by Unity Catalog permissions, queryable from Databricks SQL or MLflow Python SDK.

  15. 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.

  16. Version 18.1

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

  17. Sample Data Explorer is generally available

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

  18. Workspace skills for Genie Code are now available

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

  19. Databricks Assistant is now Genie Code

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

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  21. Version 18.0

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

  22. Serverless environment version 5 is now available

    Includes CPU and GPU versions.

  23. Connect Databricks Assistant to MCP servers

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

  24. 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)
  25. Serverless workspaces are now generally available

    Come pre-configured with serverless compute and default storage.

  26. 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.

  27. Create skills for Databricks Assistant

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

  28. Databricks Assistant Agent mode is now in Public Preview

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

  29. 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)
  30. Serverless notebook tasks can now use jobs environment

    Replaces inherited serverless environment with configurable job environment.

  31. Serverless compute has been updated to version 17.3

    Updated from version 17.2, requires no configuration changes.

  32. 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.

  33. 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)
  34. Notebook improvements

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

  35. 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.

  36. 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.

  37. Databricks Assistant integrated with compute

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

  38. Databricks-hosted models for Assistant are now GA

    Available on all cloud platforms at no extra cost.

  39. Databricks Assistant: User and workspace instructions now available

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

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

    Performs reasoning and editing across multiple cells without manual intervention.

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.