Skip to content

Databricks releases, every cloud

10 releases of 1321

Last updated

  1. JAR tasks on serverless compute are now generally available

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

  2. 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.

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

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

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

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

  5. 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.

  6. 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.

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

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

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

  10. 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.

  11. Serverless workspaces are now generally available

    Come pre-configured with serverless compute and default storage.

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.