Databricks releases, every cloud

1. Agentic code converter is in Beta

   Converts T-SQL, Snowflake, and other dialects to ANSI SQL. Requires workspace admin enablement.

   #Migration
   AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) Jul 16, 2026
2. Databricks Runtime 19 and Databricks Runtime 19 for Machine Learning are in Beta

   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) Jun 15, 2026
3. Databricks Runtime 18 and Databricks Runtime 18 for Machine Learning are in Beta

   Powered by Apache Spark 4.1.0, replacing separate release notes for feature versions.

   #Databricks Runtime
   AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) May 22, 2026
4. Databricks Runtime 18.2 and Databricks Runtime 18.2 ML are in Beta

   Powered by Apache Spark 4.1.0.

   #Databricks Runtime
   AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) Apr 8, 2026
5. Databricks Runtime 18.1 and Databricks Runtime 18.1 ML are in Beta

   Powered by Apache Spark 4.1.0.

   #Databricks Runtime
   AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown) Feb 17, 2026
6. 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
   AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown) Dec 9, 2025
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 17.3 LTS and Databricks Runtime 17.3 LTS ML are in Beta

   Powered by Apache Spark 4.0.0, includes new configuration options.

   #Databricks Runtime
   AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown) Oct 6, 2025
9. Admins can now manage a workspace's serverless base environments (Public Preview)

   Defines custom environment specs for serverless notebooks, allows setting a default for new notebooks.

   #Notebooks#Serverless
   AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown) Aug 28, 2025

Headlines, dates and product areas are Databricks' own, and every item links to the note it came from. The one-line summaries are ours.