Databricks Release Notes

The managed Notion connector in Lakeflow Connect is now available in Beta. The connector ingests pages, data sources, databases, blocks, comments, and users from Notion into Databricks. See Notion connector.

You can now run a continuous Lakeflow pipeline with a continuous job. When a continuous job orchestrates a pipeline, the job determines the execution mode, and the pipeline can use job-level features such as serverless Standard performance mode and additional notification destinations. Databricks recommends this pattern over the pipeline's built-in continuous setting, which is not being removed.

See Run a continuous pipeline with a continuous job and Run a pipeline continuously with a continuous job.

The system.alert schema is in Public Preview. This schema contains the alerts table, which records the configuration of every alert, and the alert_evaluation_history table, which records one row per alert evaluation. Use these tables to audit alert definitions, analyze evaluation trends, and monitor alert workloads at scale.

See Alert system tables reference.

Tag automations are now in Beta. A tag automation assigns or removes governed tags on the Unity Catalog tables or volumes that match conditions you define, so tags stay accurate as your data and metadata change. Use them to certify trusted data, deprecate stale data, roll up column sensitivity to a table-level tier, flag assets that are missing required tags, and clean up outdated tags.

You can build an automation by describing your rule to Genie in natural language, or by filling in the scope, conditions, and action yourself. Saving an automation starts a dry run, which records the assets it would match without assigning any tags.

See Automate tag assignment.

You can now read a change data feed from a materialized view created in a Lakeflow pipeline or in Databricks SQL, using Databricks Runtime 18 LTS or above. Use this to replicate materialized view changes to destinations outside Databricks, or to keep a history of materialized view changes for auditing and reporting. Materialized views use automatic change data feed, so the change data feed is available for any materialized view with row tracking enabled, without configuring each materialized view. This feature is in Beta.

See Read a change data feed from a materialized view.

Package Scala or Java code as a JAR and run it as a task in a Lakeflow Job on serverless compute. Your JAR must match the Scala, Java Development Kit (JDK), and Databricks Connect versions of your serverless environment version. See Create and run JARs on serverless compute.

All Databricks-managed MCP connectors for Genie One and Genie Code have migrated to the Unity Gateway. This brings Databricks-managed connectors under Unity Gateway, enabling centralized governance, access controls, and visibility alongside your other MCP servers and tools.

Users must reauthenticate their connectors to continue using them with Genie One and Genie Code. A notification in Genie prompts impacted users to reconnect.

Moonshot AI Kimi K3 is now available on Unity Gateway for long-horizon coding, knowledge work, and reasoning, with native vision. Access it through the same governed API as other models, with centralized permissions, guardrails, spend controls, and observability, and switch models without changing application code.

To query the model and see supported regions, see Use foundation models.

The Zerobus Ingest connector in Lakeflow Connect is now enabled by default for workspaces with the compliance security profile enabled. See Zerobus Ingest overview.

Genie Code can now search the public web to answer questions that need current information. Web search is disabled by default during the beta for eligible workspaces and must be turned on from the Previews page. See Search the web.

Lakebase is now enabled by default in workspaces with the compliance security profile, including workspaces that use the HIPAA, C5, or TISAX standard and workspaces that enable the profile without a compliance standard. You no longer need to enable Lakebase in these workspaces. See Data protection.

REPLACE USING flows are now available in Lakeflow pipelines in Beta.

Use a REPLACE USING flow when your source is a series of partial snapshots keyed by column. On each update, the flow replaces all rows that match the specified key columns and leaves all other rows unchanged. A SEQUENCE BY column orders the updates, so the highest sequence for a key always wins, even when updates arrive out of order. REPLACE USING doesn't require a change data capture feed with explicit insert, update, and delete operations, and it doesn't require a primary key.

See Partial snapshot replacement with REPLACE USING flows.

You can now search and replace text across files in a Databricks Git folder or Declarative Automation Bundles project from the Search pane. See Search and replace across files.

You can now use Genie One directly in the Databricks Connector for Google Sheets. Query your governed Databricks data in natural language and import the results into Google Sheets as native rows and columns. See Use Genie One in Google Sheets.

You can now use Genie One directly in the Databricks Excel Add-in. Query your governed Databricks data in natural language and import the results into Microsoft Excel as native rows and columns. See Use Genie One in Microsoft Excel.

Unity Gateway is now generally available. Unity Gateway is the Databricks governance solution for enterprise AI, part of Unity Catalog. With Unity Gateway you can:

• Control which AI services teams can use.
• Route and manage AI traffic across providers.
• Govern MCP servers to control access and costs.
• Monitor usage, cost, access, and lineage from one place.

Some capabilities, including service policies and agent services, remain in Beta.

See AI governance with Unity Gateway and AI governance guide.

Sharing Delta tables with Iceberg reads enabled is now generally available. See Delta Lake feature support matrix.

Sharing Delta tables with deletion vectors or column mapping enabled is now generally available. See Add tables with deletion vectors or column mapping to a share.