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31 releases of 1321

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  1. Incremental ingestion for Salesforce formula fields in Lakeflow Connect will soon be generally available Coming soon

    Replaces full snapshot default, improving performance and reducing cost.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  2. Apache Arrow support for Zerobus Ingest is now generally available

    Replaces JSON and Avro formats, requires Lakeflow Connect.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  3. 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)
  4. Zerobus Ingest into streaming tables is now generally available

    Works like writing to a managed Delta table with same limits and quotas.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  5. Salesforce connector mTLS authentication is now generally available

    Replaces OAuth client credentials flow for API-only users, requires client certificates.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  6. JAR tasks on serverless compute are now generally available

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

    #Lakeflow#Serverless
    AWS, read it on their docsAzure, read it on their docsGCP, 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. 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)
  9. MLflow trace storage in Unity Catalog is now generally available

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

    #MLflow#Unity Catalog
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  10. REPLACE WHERE flows are now generally available

    Replaces full table reprocessing with row-level updates based on a predicate.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  11. Lakeflow Connect row filtering is now generally available

    Works like a SQL WHERE clause, applies to initial and incremental updates.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  12. SQL alert task in Lakeflow Jobs is now generally available

    Evaluates a Databricks SQL alert as part of a Lakeflow Job, returning its state for downstream tasks.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  13. The update_flow API for Spark Declarative Pipelines on Lakeflow is generally available

    Writes to a sink in update output mode, emitting only changed rows. Supports stateful aggregations without a watermark.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  14. Query-based connectors for Lakeflow Connect are now generally available

    Ingests data from databases like Oracle and PostgreSQL without CDC configuration.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  15. Refresh policies and EXPLAIN CREATE MATERIALIZED VIEW for materialized views are now generally available

    Requires Databricks Runtime 17.3 and above. Available in Databricks SQL.

    #Databricks SQL#Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  16. Unified runs list is generally available

    Replaces separate job and pipeline run lists, adds filtering and error code visualization.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  17. Spark Declarative Pipelines on Lakeflow sinks are now generally available

    Supports writing to Delta tables, Kafka topics, and Azure Event Hubs.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  18. 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)
  19. Lakeflow Pipelines Editor is now generally available

    Offers agent-first experience with Genie Code for creating production pipelines.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  20. Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
  21. Disabling tasks in Lakeflow Jobs is now GA

    Disabled tasks retain config and run history, can be re-enabled later.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  22. 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)
  23. COMMENT ON streaming tables is now GA

    Adds comments to streaming tables, previously only available for non-streaming tables.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  24. Applying filters, masks, tags, and comments to pipeline-created datasets is now GA

    Modifies ETL and ingestion pipelines using CREATE, ALTER, or Lakeflow UI. Applies to Spark Declarative Pipelines on Lakeflow and Lakeflow Connect.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  25. 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)
  26. Updated Lakeflow Jobs UI is generally available

    Simplifies job creation and editing, see Lakeflow Jobs for details.

    #Lakeflow
    AWS(not on this cloud)Azure, read it on their docsGCP(not on this cloud)SAP(unknown)
  27. Spark Declarative Pipelines on Lakeflow stream progress metrics are generally available

    Supports querying event log for stream progress metrics.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  28. 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)
  29. Migrate Spark Declarative Pipelines on Lakeflow pipelines from legacy publishing mode is generally available

    Replaces legacy mode that only published to a single catalog and schema. Now supports multiple catalogs and schemas.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  30. 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)
  31. Migrate Spark Declarative Pipelines on Lakeflow from legacy publishing mode is now GA

    Replaces legacy single-catalog publishing with multi-catalog support.

    #Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  32. 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)
  33. Moving tables between Spark Declarative Pipelines on Lakeflow pipelines is now GA

    Supports moving tables in Unity Catalog ETL pipelines.

    #Lakeflow
    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.