Skip to content

Databricks releases, every cloud

117 releases of 1321

Last updated

  1. Base environments are now supported on classic compute (Beta)

    Manages Python dependencies using Databricks-provided or custom environments.

  2. The counter_diff SQL window function is now available

    Calculates differences between consecutive cumulative counter values, available in Databricks Runtime 19 and above.

  3. Window measures on a numeric index column in metric views

    Supports unitless offset and ranges on consecutive integer columns, useful for non-calendar periods like fiscal weeks.

  4. Session restore for serverless jobs is in Public Preview

    Restores Python variables and Spark session into a new notebook for debugging or exploration, requires eligible serverless compute job runs.

  5. Standard performance mode is now available for one-time runs in the Jobs API

    Sets performance_target to STANDARD. Supports Apache Airflow's DatabricksSubmitRunOperator.

  6. See which chunks support each ai_search answer (Beta)

    Added generate_citations option to show supporting chunks.

  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. time_bucket SQL function aligns timestamps to fixed-width time buckets

    Replaces date_trunc for non-calendar units, requires origin and width parameters.

  9. Environment version 6 is now available

    Supports serverless and standard classic compute.

  10. Manage project environments with %uv commands

    Requires environment version 5 or above. Supports serverless notebooks.

  11. Session restore for serverless jobs is now in Beta

    Restores Python variables and Spark session into a new notebook. Captures state snapshots on failure or long runs.

  12. REPLACE USING flows for standalone streaming tables (Beta)

    Replaces rows matching specified key columns, requires SEQUENCE BY column.

  13. Alert system tables are in Public Preview

    Contains alerts and alert_evaluation_history tables for auditing and monitoring.

  14. Change data feed on materialized views (Beta)

    Requires Databricks Runtime 18 LTS or above. Enables replication to external destinations.

  15. JAR tasks on serverless compute are now generally available

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

  16. Search and replace text across files

    Works in Databricks Git folders or Declarative Automation Bundles projects from the Search pane.

  17. Automatic cost attribution for materialized views and streaming tables in Databricks SQL

    Inherits custom tags from enclosing SQL warehouse environment for billing.

  18. Organize your work with spaces

    Preserves open tabs for specific folders or projects.

  19. 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.

  20. Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
  21. Git CLI commands in Git folders are now in Public Preview

    Enables standard Git commands like git stash and rebase in Databricks terminals. Requires workspace eligibility.

  22. Warehouse-level statement timeouts (Beta)

    Set via statement_timeout field in Create or Update warehouse APIs.

  23. Mention Genie Code in notebook comments

    Triggers AI help inline by typing @ and selecting Genie Code.

  24. Databricks SQL alerts are now available by default for workspaces with the compliance security profile enabled

    Supports all compliance security profile standards, monitors data and KPIs via scheduled queries.

  25. July 6, 2026

    Updates from Databricks Runtime 18, adds Spark Declarative Pipelines and IP address functions.

  26. Lakehouse Real-Time (Beta)

    Delivers sub-second SQL read queries against Unity Catalog tables. Built for low-latency workloads.

  27. MATCH_RECOGNIZE is now in Beta

    Requires enabling Match Recognize preview in workspace settings.

  28. Databricks SQL version 2026.20 is now available in Preview

    Adds IP address functions, NEAREST BY join type, and QUALIFY clause, with fixes for MERGE WITH SCHEMA EVOLUTION.

  29. Metric view parameters are now in Public Preview

    binds values at query time, replacing separate views per variant.

  30. 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.

  31. Lakehouse Replay (Beta)

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

  32. Reorganized Spark Declarative Pipelines on Lakeflow documentation

    Conceptual topics are now under Concepts.

  33. UNIQUE constraint support is now in Public Preview

    Enables join elimination and DISTINCT simplification on Photon-enabled compute. Applies to Unity Catalog Delta Lake tables.

  34. 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.

  35. Workspace admin setting for serverless notebook execution timeout

    Replaces manual override process, defaults to 2.5 hours.

  36. Databricks SQL version 2026.15 is now available in Preview

    XPath no longer fetches external DTDs, fixing failures from malformed URLs.

  37. Fixed LOD expression syntax update for metric views

    Uses SQL window functions, replacing two-step pre-computation approach.

  38. Databricks SQL alerts are now generally available

    Monitors data and KPIs by running scheduled queries, notifying recipients when conditions are met.

  39. Version 18.2

    Adds CREATE OR REPLACE TEMP TABLE syntax and upgrades Snowflake JDBC driver to 3.28.0.

  40. Faster package installs with %uv pip in serverless notebooks

    Requires environment version 5 or above. Replaces %pip for faster installs.

  41. Native data profiling for notebook results tables

    View column statistics by selecting headers and clicking Open selection details. Available in notebooks and new SQL editor.

  42. Native data profiling for results tables in the SQL editor

    Select column headers and click Open selection details to view statistics.

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.