Databricks releases, every cloud
- Workspace admin setting for serverless notebook execution timeout
Replaces manual override process, defaults to 2.5 hours.
- Databricks SQL version 2026.15 is now available in Preview
XPath no longer fetches external DTDs, fixing failures from malformed URLs.
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 parameters are now in Beta
Define key-value pairs at pipeline level, referenced in SQL using named parameter syntax.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Postgres password authentication is now disabled by default for new Lakebase projects
Existing projects are unaffected, enable in project settings to allow.
- Customer-managed keys for Lakebase available in all AWS and Azure regions
Encrypts project data at rest using a custom cloud KMS key. Available for new projects.
- Fixed LOD expression syntax update for metric views
Uses SQL window functions, replacing two-step pre-computation approach.
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- Lakebase now supports compute sizes up to 64 CU (128 GB)
Replaces 32 CU (64 GB RAM) limit, enables dynamic scaling for larger workloads.
- Unified runs list is generally available
Replaces separate job and pipeline run lists, adds filtering and error code visualization.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Recover a deleted Lakebase project within 7 days
Restores all branches, databases, and settings. Requires action within 7 days.
- Spark Declarative Pipelines on Lakeflow sinks are now generally available
Supports writing to Delta tables, Kafka topics, and Azure Event Hubs.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks SQL alerts are now generally available
Monitors data and KPIs by running scheduled queries, notifying recipients when conditions are met.
- Spark Declarative Pipelines on Lakeflow environment versions (Beta)
Pins Python version and libraries, decoupling from Databricks Runtime upgrades.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - SQL alert task in Lakeflow Jobs is now in Public Preview
Evaluates a Databricks SQL alert as part of a Lakeflow Job, returning its state as output.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - New Lakebase instances now scale to zero by default
New instances scale to zero after 24 hours of inactivity, reducing compute costs. Existing projects are unaffected.
- Version 18.2
Adds CREATE OR REPLACE TEMP TABLE syntax and upgrades Snowflake JDBC driver to 3.28.0.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Lakebase Change Data Feed (CDF) is now in Public Preview
Captures row-level changes from Postgres tables as Delta tables, requiring no external CDC stack.
- HubSpot connector (GA)
Ingests data from HubSpot Marketing Hub into Databricks.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Faster package installs with %uv pip in serverless notebooks
Requires environment version 5 or above. Replaces %pip for faster installs.
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- Standalone pipelines on serverless general compute (Beta)
Requires serverless general compute, created via SQL or Python.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - GitHub managed ingestion connector (Beta)
ingests GitHub data into Databricks, available in Lakeflow Connect.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Outlook managed ingestion connector (Beta)
Ingests email data from Microsoft Outlook into Databricks.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Smartsheet managed ingestion connector (Beta)
Ingests Smartsheet data into Databricks, available in Lakeflow Connect.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Lakeflow Pipelines Editor is now generally available
Offers agent-first experience with Genie Code for creating production pipelines.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Community connectors (Beta)
Extends Lakeflow Connect to unsupported sources, built by the community.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Native data profiling for results tables in the SQL editor
Select column headers and click Open selection details to view statistics.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Upcoming change: Upgrade to Lakebase Autoscaling Coming soon
Upgrades start in June 2026, replacing Provisioned instances with autoscaling, requiring updated connection strings for some Private Link setups.
- agg SQL function as a synonym for measure
Replaces measure, used as agg(measure_column) in metric views.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Disabling tasks in Lakeflow Jobs is now GA
Disabled tasks retain config and run history, can be re-enabled later.
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 (Public Preview)
Provides 512 workers, available in all 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) - Zendesk Support connector (GA)
Allows syncing Zendesk tickets to Databricks.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Confluence connector (GA)
Allows reading Confluence spaces and pages into Databricks.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Workspace base environments are now generally available
Lets workspace admins create pre-built environments for serverless notebooks, enabled by default in compliance security profile workspaces.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this 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) - Lakeflow Designer is now in Public Preview
Offers drag-and-drop canvas and natural language for building data workflows.
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) - Query-based connectors for Lakeflow Connect (Public Preview)
Ingests data from databases using a cursor column, supporting Oracle, Teradata, and others.
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.
- New cascade field for deleting Unity Catalog pipelines (Beta)
Deletes associated materialized views and tables by default, set cascade=false to retain them.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Upcoming breaking change: default behavior when deleting a Unity Catalog pipeline Coming soon
Deletes now retain associated tables by default, set cascade=true to remove them.
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.