Databricks releases, every cloud
- 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.
- JAR tasks on serverless compute are now generally available
Requires matching Scala, Java Development Kit, and Databricks Connect versions.
- 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.
- Databricks Runtime 19 and Databricks Runtime 19 for Machine Learning are now generally available
Powered by Apache Spark 4.2.0.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 18.2 is now GA
Replaces 7.3 and 7.3 ML.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Workspace base environments are now generally available
Lets workspace admins create pre-built environments for serverless notebooks, enabled by default in compliance security profile workspaces.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- 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) - Serverless workspaces are now generally available
Come pre-configured with serverless compute and default storage.
- Databricks Runtime 18.0 is now GA
Replaces Databricks Runtime 7.3.
- Databricks Runtime 17.3 LTS is now GA
Replaces 7.3 LTS, requires Databricks account.
- Databricks Runtime 17.2 is now is now GA
Replaces 7.3 and earlier, requires new cluster creation.
- Databricks Runtime 17.1 is now is now GA
Replaces Databricks Runtime 7.3.
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.