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Databricks releases, every cloud

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14 releases of 1321

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  1. Automatic change data feed is now generally available

    Requires Databricks Runtime 19 or above with row tracking enabled. Makes MERGE and UPDATE operations about 15% faster.

    #Databricks Runtime
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  2. Databricks Runtime 19 and Databricks Runtime 19 for Machine Learning are now generally available

    Powered by Apache Spark 4.2.0.

    #Databricks Runtime
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  3. Scala and Java UDFs in Unity Catalog are now generally available

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

    #Data Engineering
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP, read it on their docs
  4. 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.

    #Data Engineering
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP, read it on their docs
  5. 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.

    #Data Engineering#Databricks SQL
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  6. 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.

    #Data Engineering
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP, read it on their docs
  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. Converting a partitioned table to liquid clustering is generally available

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

    #Data Engineering
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP, read it on their docs
  9. Databricks Runtime 18.2 is now GA

    Replaces 7.3 and 7.3 ML.

    #Databricks Runtime
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  10. Databricks Runtime 18.1 is now GA

    Replaces Databricks Runtime 7.3.

    #Databricks Runtime
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  11. Serverless workspaces are now generally available

    Come pre-configured with serverless compute and default storage.

    #Serverless#Workspace
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  12. Databricks Runtime 18.0 is now GA

    Replaces Databricks Runtime 7.3.

    #Databricks Runtime
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  13. Databricks Runtime 17.3 LTS is now GA

    Replaces 7.3 LTS, requires Databricks account.

    #Databricks Runtime
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  14. Databricks Runtime 17.2 is now is now GA

    Replaces 7.3 and earlier, requires new cluster creation.

    #Databricks Runtime
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  15. Databricks Runtime 17.1 is now is now GA

    Replaces Databricks Runtime 7.3.

    #Databricks Runtime
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(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.