Databricks releases, every cloud
| Release | Date | ||||
|---|---|---|---|---|---|
| Lakehouse Replay (Beta) Automatically replays serverless workloads against upcoming runtime releases. Requires no setup. | On AWS, read it on their docs | On Azure, read it on their docs | On GCP, read it on their docs | Not on SAP | Jun 10, 2026 |
| Reorganized Spark Declarative Pipelines on Lakeflow documentation Conceptual topics are now under Concepts. | On AWS, read it on their docs | On Azure, read it on their docs | On GCP, read it on their docs | Not on SAP | Jun 9, 2026 |
| Spark Declarative Pipelines on Lakeflow updates are retained for 60 days Retention period increased from 30 to 60 days, applying to UI and REST API updates. | On AWS, read it on their docs | On Azure, read it on their docs | On GCP, read it on their docs | Not on SAP | Apr 28, 2026 |
| SQL alert task for jobs (Beta) Evaluates SQL alerts as part of workflows, enabling automated condition checks and notifications. | On AWS, read it on their docs | On Azure, read it on their docs | On GCP, read it on their docs | Not on SAP | Mar 19, 2026 |
- Lakehouse Replay (Beta)
Automatically replays serverless workloads against upcoming runtime releases. Requires no setup.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Reorganized Spark Declarative Pipelines on Lakeflow documentation
Conceptual topics are now under Concepts.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Spark Declarative Pipelines on Lakeflow updates are retained for 60 days
Retention period increased from 30 to 60 days, applying to UI and REST API updates.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - SQL alert task for jobs (Beta)
Evaluates SQL alerts as part of workflows, enabling automated condition checks and notifications.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
Headlines, dates and product areas are Databricks' own, and every item links to the note it came from. The one-line summaries are ours.