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Databricks releases, every cloud

174 releases of 1354

Last updated

  1. Google Ads connector (Beta)

    Ingests data from Google Ads into Databricks via Lakeflow Connect.

  2. Zendesk Support connector (Beta)

    Ingests ticket, help center, and community forum data from Zendesk Support.

  3. Trigger on update for pipelines (GA)

    Refreshes pipeline when source table changes, usable in Databricks SQL pipeline schedules.

  4. View and restore your recent workspace tab sessions

    Restores up to 10 recent sessions.

  5. Serverless workspaces are now generally available

    Come pre-configured with serverless compute and default storage.

  6. Google Drive connector (Beta)

    Supports read_files, spark.read, COPY INTO, and Auto Loader for ingesting files.

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

  9. Ingest Salesforce formula fields incrementally (Beta)

    Replaces snapshotting with incremental ingestion, improving performance and reducing costs.

  10. Row filtering for managed ingestion connectors (Beta)

    Applies conditions like a SQL WHERE clause, available for Google Analytics, Salesforce, and ServiceNow connectors.

  11. Meta Ads connector (Beta)

    Ingests data from Meta Ads, requires setup as a data source.

  12. MySQL connector in Lakeflow Connect (Public Preview)

    Enables incremental data ingestion from various MySQL databases. Requires access request through account team.

  13. Confluence connector (Beta)

    Ingests Confluence spaces and pages into Databricks, requires OAuth U2M configuration.

  14. PostgreSQL connector in Lakeflow Connect (Public Preview)

    Enables incremental data ingestion from various PostgreSQL databases. Requires configuration.

  15. Change owner for materialized views or streaming tables defined in Databricks SQL

    Done through Catalog Explorer, replacing previous methods.

  16. Customizable SharePoint connector (Beta)

    Ingests structured, semi-structured, and unstructured files into Delta tables with customizable schema inference and parsing options.

  17. Discover files in Auto Loader efficiently using file events

    Requires file events enabled on external locations. Replaces directory listing for efficiency.

  18. Jira connector (Beta)

    Ingests Jira issues, comments, and attachments metadata into Databricks.

  19. Microsoft Dynamics 365 connector (Public Preview)

    Ingests data from Dynamics 365 apps into Databricks. Requires Lakeflow Connect.

  20. Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
  21. NetSuite connector (Public Preview)

    Ingests data from NetSuite2.com via API, CLI, or notebook.

    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(unknown)
  22. ForEachBatch for Spark Declarative Pipelines on Lakeflow is available (Public Preview)

    Allows processing streams as micro-batches in Python. Requires Lakeflow setup.

  23. Spark Declarative Pipelines on Lakeflow stream progress metrics are generally available

    Supports querying event log for stream progress metrics.

  24. Configure full refresh behavior for managed database connectors

    Applies to Lakeflow Connect managed database connectors, allowing scheduled full refresh snapshots and automatic recovery from unsupported schema changes.

  25. Jobs can now be triggered on source view update

    Supports views referencing supported table types, see documentation for specifics.

  26. Improved full refresh flow for managed database connectors

    Reduces downtime by delaying table refresh until snapshot completion, minimizing PENDING_RESET errors.

  27. SFTP connector (Public Preview)

    Extends Auto Loader to ingest files from SFTP servers.

  28. Lakeflow Declarative Pipelines has been renamed to Lakeflow Spark Declarative Pipelines

    Replaces Lakeflow Declarative Pipelines, see Spark Declarative Pipelines for details.

  29. Serverless notebook tasks can now use jobs environment

    Replaces inherited serverless environment with configurable job environment.

  30. JAR tasks are now supported on serverless compute

    Run JAR jobs without a cluster.

  31. Salesforce ingestion connector supports history tracking (SCD type 2)

    Enables history tracking, overwriting default SCD type 1 behavior.

  32. Serverless compute has been updated to version 17.3

    Updated from version 17.2, requires no configuration changes.

  33. Zerobus Ingest connector in Lakeflow Connect (Public Preview)

    Enables record-by-record ingestion into Delta tables via gRPC API.

    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(unknown)
  34. Unified runs list (Public Preview)

    Combines job and pipeline runs into one list.

  35. Jobs can now be triggered on source table update

    Triggers require Databricks Runtime 7.0 or later.

  36. Create backfill job runs

    Triggers job runs to load past data, useful for repairing processing failures.

  37. 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.

  38. Lakeflow Pipelines Editor is now in public preview

    Replaces multi-file editor, edits pipelines as files in asset browser, defaults to Python and SQL code.

  39. New requirement to create connections for Salesforce ingestion

    Requires Databricks connected app installed. Applies to new connections only.

  40. 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.

  41. Discover files in Auto Loader efficiently using file events without enrollment (Public Preview)

    Requires file events enabled on external locations.

  42. Google Analytics Raw Data connector GA

    Enables ingestion of raw Google Analytics data into Databricks, requires Google Analytics 4 and Google BigQuery setup.

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