Databricks releases, every cloud Sep 2025 Jan 2026 May 2026 Sep 2026
5
releases of 1321
All time Last updated 13 hours ago
Released on
Not yet on
Product
Release AWS Azure GCP SAP Date Automated setup for S3 external locations Uses AWS IAM temporary delegation to configure external locations and provision required resources.
On AWS, read it on their docs − Not on Azure − Not on GCP On SAP, read it on their docs Jul 22, 2026 Workspace admin setting for serverless notebook execution timeout Replaces manual override process, defaults to 2.5 hours.
On AWS, read it on their docs On Azure, read it on their docs On GCP, read it on their docs On SAP, read it on their docs May 27, 2026 Fixed LOD expression syntax update for metric views Uses SQL window functions, replacing two-step pre-computation approach.
On AWS, read it on their docs On Azure, read it on their docs On GCP, read it on their docs On SAP, read it on their docs May 20, 2026 Faster package installs with %uv pip in serverless notebooks Requires environment version 5 or above. Replaces %pip for faster installs.
On AWS, read it on their docs On Azure, read it on their docs On GCP, read it on their docs On SAP, read it on their docs May 7, 2026 Search in metric views fix Now returns correct results across paginated results and supports filtering by display name.
On AWS, read it on their docs On Azure, read it on their docs On GCP, read it on their docs On SAP, read it on their docs Mar 17, 2026
Automated setup for S3 external locations Uses AWS IAM temporary delegation to configure external locations and provision required resources.
Workspace admin setting for serverless notebook execution timeout Replaces manual override process, defaults to 2.5 hours.
Fixed LOD expression syntax update for metric views Uses SQL window functions, replacing two-step pre-computation approach.
Faster package installs with %uv pip in serverless notebooks Requires environment version 5 or above. Replaces %pip for faster installs.
Search in metric views fix Now returns correct results across paginated results and supports filtering by display name.
Headlines, dates and product areas are Databricks' own, and every item links to the note it
came from. The one-line summaries are ours.