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Databricks releases, every cloud

16 releases of 1321

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  1. 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.

  2. Environment variables for serverless jobs are in Beta

    Requires workspace admin to enable from Previews page.

  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. Object metadata column is now in Public Preview

    Exposes object properties like MIME type and tags, available in Databricks Runtime 18.1.

  6. MySQL integrated CDC pipeline is now in Beta

    Replaces separate ingestion gateway, requires single pipeline update.

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

  9. 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.

  10. 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.

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

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

  12. Lakehouse Replay (Beta)

    Automatically replays serverless workloads against upcoming runtime releases. Requires no setup.

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

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

  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. Spark Declarative Pipelines on Lakeflow updates are retained for 60 days

    Retention period increased from 30 to 60 days, applying to UI and REST API updates.

  16. SQL alert task for jobs (Beta)

    Evaluates SQL alerts as part of workflows, enabling automated condition checks and notifications.

  17. Store and query MLflow traces in Unity Catalog (Beta)

    Stores MLflow traces in Delta tables for long-term retention and analysis using OpenTelemetry format.

    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(unknown)

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.