Databricks releases, every cloud
- Databricks Runtime maintenance updates (04/20)
Includes bug fixes, security patches, and performance improvements for versions 13.3 to 18.1.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Version 18.1
Supports DATETIMEOFFSET for Azure Synapse and adds schema evolution with INSERT statements.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 18.2 and Databricks Runtime 18.2 ML are in Beta
Powered by Apache Spark 4.1.0.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 18: April 2, 2026
Adds VOID column support in UDTs and 30-second socket timeout for JDBC streaming sink connections.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime maintenance updates (04/02)
Includes bug fixes, security patches, and performance improvements for versions 13.3 to 18.1.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - AI Runtime is now in Public Preview
Adds GPU support to serverless compute for deep learning workloads.
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- Databricks Runtime 18: March 11, 2026
Replaces previous behavior where observation metric errors caused query failures.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 18.1 is now GA
Replaces Databricks Runtime 7.3.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 18: March 10, 2026
Includes clearer error messages for scalar subqueries and operating system security updates.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime maintenance updates (03/10)
Includes bug fixes, security patches, and performance improvements for versions 13.3 to 18.0.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Declarative Feature Engineering APIs (Beta)
Define time-windowed aggregation features from data sources, materialize to Delta tables or Lakebase. Available in us-east-1 and us-west-2 regions.
- Endpoint telemetry for custom model serving endpoints (Beta)
Stores logs, traces, and metrics in Unity Catalog Delta tables using OpenTelemetry.
- Serverless compute now available for IRAP and Canada Protected B workloads on Azure Databricks
Requires environment version 5 to be enabled.
- Version 18.0
Upgrades Redshift JDBC driver to 2.1.0.28, adds SQL window functions to metric views.
- Databricks Runtime 18: February 26, 2026
Adds SET and UNSET METADATA ON COLUMN SQL commands for Unity Catalog table columns. Includes OS security updates.
- Databricks Runtime maintenance updates (02/26)
Includes bug fixes, security patches, and performance improvements for versions 12.2 to 18.0.
- Serverless environment version 5 is now available
Includes CPU and GPU versions.
- Databricks Runtime 18: February 19, 2026
Inferencing Excel string cells now respects cell type, updating from auto-casting to narrower types.
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- Databricks Runtime maintenance updates (02/19)
Includes bug fixes, security patches, and performance improvements for versions 12.2 to 18.0.
- Databricks Runtime 18.1 and Databricks Runtime 18.1 ML are in Beta
Powered by Apache Spark 4.1.0.
- Serverless compute now available for compliance standards
Adds HITRUST, PCI-DSS, TISAX, and UK Cyber Essentials Plus support.
- New GCP regions support serverless compute
Available in me-central1 and southamerica-east1 regions.
- Serverless workspaces are now generally available
Come pre-configured with serverless compute and default storage.
- Databricks Runtime 18: January 27, 2026
Reports batchSize and file processing metrics, renames spark.sql.xml.legacyXMLParser.enabled config property.
- Databricks Runtime maintenance updates (01/27)
Includes bug fixes, security patches, and performance improvements for versions 12.2 to 18.0.
- 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.
- Databricks Runtime 18: January 15, 2026
Uses JDK 21, replacing JDK 17, with changes to Double and Float string representations.
- Databricks Runtime 18.0 is now GA
Replaces Databricks Runtime 7.3.
- Databricks Runtime maintenance updates (01/09)
Includes bug fixes, security patches, and performance improvements for versions 12.2 to 17.3.
- Serverless compute is now available in Azure China North 3
Available for notebooks, jobs, pipelines, and SQL warehouses.
- Serverless workspaces are now available in new GCP regions
Available in most GCP regions, see documentation for list.
- Databricks Runtime 18.0 and Databricks Runtime 18.0 ML are in Beta
Powered by Apache Spark 4.1.0, includes JDK 21 as default.
- Databricks Runtime maintenance updates (12/09)
Includes bug fixes, security patches, and performance improvements for versions 12.2 to 17.3.
- Serverless compute is now available in new regions
Added to Australia Southeast, Canada Central, Mexico Central, Norway East, and South Africa North regions.
- Databricks Runtime maintenance updates (11/18)
Includes bug fixes, security patches, and performance improvements for versions 12.2 to 17.3.
- Serverless notebook tasks can now use jobs environment
Replaces inherited serverless environment with configurable job environment.
- Databricks Runtime maintenance updates (11/04)
Includes bug fixes, security patches, and performance improvements for versions 12.2 to 17.3.
- Serverless compute has been updated to version 17.3
Updated from version 17.2, requires no configuration changes.
- Databricks Runtime 17.3 LTS is now GA
Replaces 7.3 LTS, requires Databricks account.
- Databricks Runtime maintenance updates (10/21)
Includes bug fixes, security patches, and performance improvements.
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.