Releasesby GlyphStandard performance mode is now supported for materialized view or streaming table refreshes in jobs
Materialized view and streaming table refreshes that are orchestrated through a SQL task in a Lakeflow job now respect the job's Performance optimized setting. When the setting is turned off, the refresh uses standard performance mode, which consumes fewer DBUs.
Also shipped Jul 6, 2026Databricks in July 2026 →
You can use Gemini in Spanner Studio to fix errors in your SQL queries
You can use Gemini in Spanner Studio to fix errors in your SQL queries. When you run a query that contains an error, you can click Fix to view a line-by-line comparison of your query and a recommended correction, along with an explanation of the change. This feature is available in Preview .
Modeling
- Added support for agent-specific AI context via the omni_agent Mustache namespace, allowing you to customize AI behavior on a per-agent basis. See Optimize models for Omni AI for more information.
Self-serve identity provider changes
- New: Users with the Owner role can switch their tailnet's identity provider from the admin console for supported providers ( beta ).
AI_TRANSLATE now supports long-document translation
Snowflake Cortex AI_TRANSLATE now supports translation of up to 100,000 input tokens, enabling organizations to translate large documents and long-form text directly in Snowflake.
AlphaGenome released for Gemini Enterprise Agent Platform
AlphaGenome, Google DeepMind's state-of-the-art genomics foundation model, is now available for deployment and use with Gemini Enterprise Agent Platform. Designed to decipher the functional regulatory code of the human genome, AlphaGenome analyzes large-scale DNA sequences at single-base resolution to predict how genetic variations affect molecular and...
Gemini API developer logs now cover the Interactions API
Logs for supported Interactions API calls are now viewable in the AI Studio dashboard, making agent interactions easier to debug.
More from LakeflowEvery Lakeflow release →
REPLACE WHERE flows are now generally available
REPLACE WHERE flows for pipelines and standalone streaming tables are now generally available. Use them to replace only rows matching a predicate on each refresh, without reprocessing the full table history. See Batch processing with REPLACE WHERE flows .
Excel file format support is now available by default
Excel file format support is now available by default for all workspaces. You can ingest, parse, and query .xls , .xlsx , and .xlsm files directly using built-in support, without external libraries or manual conversions. See Read and stream Excel files .
Behavior changes for continuous jobs and pipelines
In early August 2026, continuous Lakeflow pipelines and jobs will receive updates to simplify configuration. You will be able to configure a continuous schedule directly from the pipeline page, including job-level settings such as performance mode . Configuring a continuous schedule this way wraps the pipeline in a continuous job.
Change to default pipeline editor for workspaces with the compliance security profile enabled
The Lakeflow Pipelines Editor has been generally available since May 2026. In August, it will become the default editor for developing and debugging pipelines in workspaces with the compliance security profile enabled. At that time the legacy editor will be removed.
Strac connector (Beta)
The Strac connector is now available in Lakeflow Connect in Beta . Workspace admins can control access to this feature from the Previews page. The connector ingests data-security audit events from your Strac instance into Databricks. Authentication uses a Strac API key. See Strac connector .
Lakeflow Connect row filtering is now generally available
Row filtering in Lakeflow Connect is now generally available. Row filtering allows you to ingest only the rows you need by applying conditions similar to a SQL WHERE clause, improving performance and minimizing data duplication.
Veeva Vault connector (Beta)
The Veeva Vault connector is now available in Lakeflow Connect in Beta . Workspace admins can control access to this feature from the Previews page. The connector uses Veeva's Direct Data API to ingest all standard objects, custom objects, system tables, and audit trail tables from your Vault instance into Databricks.
MySQL integrated CDC pipeline is now in Beta
The integrated CDC pipeline for MySQL is now in Beta . An integrated CDC pipeline ingests change data from MySQL into Databricks using a single pipeline, combining extraction and application into one pipeline update. Unlike the standard gateway-based architecture, an integrated CDC pipeline requires no separate ingestion gateway.