Databricks releases, every cloud
- Databricks SQL version 2026.10 is rolling out in Current
Replaces version 2026.09, requires no configuration changes.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Lakebase OpenTelemetry export (Beta)
Exports Lakebase metrics and logs to OTLP-compatible backends like Grafana Cloud or Datadog. Configured from the Lakebase App.
- Version 18.1
Supports DATETIMEOFFSET for Azure Synapse and adds schema evolution with INSERT statements.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Lakebase: Customer-managed keys
Uses a cloud KMS customer-managed key for encryption.
- Databricks Documentation site table of contents tabs
Replaces static sidebar with tabbed navigation, includes 6 context tabs.
- Databricks SQL version 2026.10 is now available in Preview
Fixes observation metric errors, optimizes Unity Catalog writes, and uses session timezone for timestamp partitions.
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
- Search in metric views fix
Now returns correct results across paginated results and supports filtering by display name.
- Lakebase databases as Databricks Apps resources
Replaces manual database configuration, requires Lakebase setup.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - 5X-Large SQL warehouse size (Beta)
Available in all supported regions, controlled from Previews page.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Lakebase updates: OAuth role management, budget policies and tags, and Lakehouse sync
Creates OAuth roles via UI or REST API, and replicates Postgres tables to Unity Catalog Delta tables.
- Lakebase now available in three additional regions
Adds Canada Central, Europe London, and South America São Paulo regions.
- Lakebase now includes high availability
Pairs primary compute with 1-3 secondary instances across zones, automatically promoting a secondary if primary fails.
- Version 18.0
Upgrades Redshift JDBC driver to 2.1.0.28, adds SQL window functions to metric views.
- Serverless environment version 5 is now available
Includes CPU and GPU versions.
- Databricks SQL version 2025.40 is rolling out in Current
Replaces version 2025.39, requires no setup changes.
- Databricks SQL version 2025.40 is now available in Preview
Adds SQL scripting with procedural logic and expands parameter markers and IDENTIFIER clause support.
- You can now use custom base environments for Python, Python Wheels, and notebook tasks in serverless jobs
Defined with YAML files, they support Python, Python wheel, and notebook tasks.
- Manage Lakebase from the Lakebase App
Replaces Compute tab navigation in Lakehouse UI, accessed via apps switcher.
- Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
- Connect to Lakebase from the SQL editor with read-write access
Supports full read-write access, see documentation for setup.
- Lakebase metrics dashboard
Monitors system and database health with metrics like RAM and CPU usage.
- Lakebase ACL support
Grants CAN CREATE or CAN MANAGE permissions from project settings.
- Databricks SQL version 2025.35 is rolling out in Current
Includes new features, see documentation for details.
- SQL Editor visualization fix
Tooltips now display in front of the legend.
- Serverless notebook tasks can now use jobs environment
Replaces inherited serverless environment with configurable job environment.
- Databricks SQL version 2025.35 is now available in Preview
Adds EXECUTE IMMEDIATE constant expressions and LIMIT ALL for recursive CTEs.
- Lakebase (Beta) now available
Adds autoscaling and database branching on AWS, separate from Public Preview.
- Serverless compute has been updated to version 17.3
Updated from version 17.2, requires no configuration changes.
- New alert editing experience
Replaces old editor with a multi-tab editor for unified workflow.
- The billable usage table now records the performance mode of serverless jobs and pipelines
Records performance mode in product_features.performance_target column with values PERFORMANCE_OPTIMIZED, STANDARD, or null.
- Visualizations fix
Fixes legend selection for charts with aliased series names in SQL editor and notebooks.
- Semantic metadata in metric views
Requires YAML 1.1 and Databricks Runtime 17.3 or higher.
- Databricks SQL version 2025.30 is now available in Preview
Adds LIKE operator support for UTF8 collations and ST_ExteriorRing function.
- OLTP Database tab renamed to Lakebase Postgres in Compute section
Used to create and manage Lakebase database instances, replacing OLTP Database tab.
- Lakebase synced tables supports syncing Apache Iceberg and foreign tables in Snapshot mode
Syncs Iceberg and foreign tables in Snapshot mode, requiring a supported Databricks runtime.
- Data type mapping update for Lakebase synced tables
Newly created synced tables map TIMESTAMP to TIMESTAMP WITH TIMEZONE. Existing tables still use TIMESTAMP WITHOUT TIMEZONE.
- Databricks SQL version 2025.25 is rolling out in Current
Rolls out from August 20th to August 28th, 2025.
- Declarative Automation Bundles support for Lakebase database resources
Defines Lakebase database catalogs, instances, and synced tables for one-command deployment. Starts instances immediately upon bundle deployment.
- Databricks SQL version 2025.25 is now available in Preview
Adds recursive common table expressions and spatial SQL expressions.
- Fixed timeout handling for materialized views and streaming tables
New views and tables apply warehouse timeout, existing ones require CREATE OR REFRESH. Default timeout is 2 days.
- Databricks Terraform provider supports Lakebase resources
Creates database catalogs, instances, and synced tables with infrastructure as code.
Headlines, dates and product areas are Databricks' own, and every item links to the note it came from. The one-line summaries are ours.