Databricks releases, every cloud
| Release | Date | ||||
|---|---|---|---|---|---|
| Git Folder Serverless is in Beta Shares serverless compute and pyproject.toml environment across notebooks and files. | On AWS, read it on their docs | On Azure, read it on their docs | On GCP, read it on their docs | Unknown on SAP | Sep 2, 2026 |
| Web terminal on serverless GPU compute (AI Runtime) is in Public Preview Runs shell commands, monitors GPU usage, and manages files on serverless GPU compute. Requires environment version 5 or above. | On AWS, read it on their docs | On Azure, read it on their docs | Not on GCP | Unknown on SAP | Jul 31, 2026 |
| Instance events and instance pools system tables are now available (Public Preview) Track instance state transitions and instance pool configurations via system.compute.instance_events and system.compute.instance_pools tables. | On AWS, read it on their docs | On Azure, read it on their docs | On GCP, read it on their docs | Not on SAP | May 21, 2026 |
| Data Classification (Public Preview) Supports all catalog types, consolidates results into a system table. | On AWS, read it on their docs | On Azure, read it on their docs | On GCP, read it on their docs | Unknown on SAP | Oct 13, 2025 |
- Git Folder Serverless is in Beta
Shares serverless compute and pyproject.toml environment across notebooks and files.
- Web terminal on serverless GPU compute (AI Runtime) is in Public Preview
Runs shell commands, monitors GPU usage, and manages files on serverless GPU compute. Requires environment version 5 or above.
- Instance events and instance pools system tables are now available (Public Preview)
Track instance state transitions and instance pool configurations via system.compute.instance_events and system.compute.instance_pools tables.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Data Classification (Public Preview)
Supports all catalog types, consolidates results into a system table.
Headlines, dates and product areas are Databricks' own, and every item links to the note it came from. The one-line summaries are ours.