Releasesby GlyphBigQuery data agent monitoring with Google Cloud Observability in preview
Teams can monitor the performance, adoption, latency and costs of BigQuery data agents and their conversations using Google Cloud Observability.
Also shipped Aug 24, 2026Google Cloud in August 2026 →
Verkada connector (Beta)
The Verkada connector is now available in Lakeflow Connect in Beta . Workspace admins can control access to this feature from the Previews page. The connector ingests organization audit logs and access users from your Verkada organization into Databricks. Authentication uses a Verkada organization API key. See Verkada connector .
Private network gateway is in Private Preview
Private network gateway is in Private Preview . A private network gateway connects Databricks serverless compute to resources in your VPC, on-premises systems, and the internet through a single managed gateway, reusing your existing network connectivity configuration (NCC).
Connect to the Databricks Genie app in Microsoft Teams with your workspace URL (Public Preview)
When you sign in to the Databricks Genie app in Microsoft Teams, you can now enter your workspace URL instead of a server hostname to connect to your Databricks account. See Databricks Genie app in Microsoft Teams .
The INSERT, UPDATE, and DELETE privileges are in Beta
The INSERT , UPDATE , and DELETE privileges are in Beta in Unity Catalog. These privileges are least-privilege alternatives to MODIFY that let you grant write access to a table's data without also granting the ability to change its schema or other metadata. The privileges require Databricks Runtime 18.1 or above.
Environment variables now use Config and Secret types
When you add or edit an environment variable in Vercel, you now choose Config or Secret instead of using the Sensitive toggle. Existing variables marked Sensitive are automatically treated as Secrets and continue to work without migration. Config: The value remains readable after saving for members with access.
Bun runtime now supports large functions and extended max duration
The Bun runtime on Vercel Functions now supports larger package sizes up to 5GB uncompressed and extended max duration for up to 30 minutes, two betas that previously ran on Node.js and Python only.
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BigQuery data governance tags are supported in Terraform
BigQuery data governance tags are supported in Terraform. This feature is in Preview .
You can now view real-time logs for your Python UDFs in Cloud Logging
You can now view real-time logs for your Python UDFs in Cloud Logging. This feature is generally available .
The Data Engineering Agent is now HIPAA compliant
The Data Engineering Agent is now HIPAA compliant . For more information, see HIPAA compliance on Google Cloud .
Core graph processing for BigQuery Graph requires an Enterprise or Enterprise Plus edition reservation
Core graph processing for BigQuery Graph requires an Enterprise or Enterprise Plus edition reservation. Existing allowlisted users can continue to use Standard edition or on-demand billing until April 26, 2027, after which these billing models will no longer be supported for core graph processing.
You can now train models using XGBoost version 2.1 by using the XGBOOST_VERSION option
You can now train models using XGBoost version 2.1 by using the XGBOOST_VERSION option. BigQuery uses the XGBoost 3.1.0 library to load and make predictions on XGBoost models. This feature is generally available .
BigQuery adds ML.TREND, ML.SEASONALITY and ML.DETECT_CHANGE_POINTS in preview
New table-valued functions in the query editor and conversational analytics identify trends, repeating seasonal patterns and structural change points in time series data.
BigQuery Graph core processing limited to Enterprise editions from April 26, 2027
Standard edition and on-demand billing support for BigQuery Graph core graph processing is deprecated, with processing restricted to Enterprise and Enterprise Plus from April 26, 2027. Graph measures remain available except in Standard edition.
The run_bq_command tool exposes the bq command-line tool within the Cloud CLI remote MCP server
The run_bq_command tool exposes the bq command-line tool within the Cloud CLI remote MCP server. AI agents can now execute advanced BigQuery operations, such as job scheduling, job management, and reservation management, through a managed MCP endpoint. For more information, see Use the Cloud CLI remote MCP server . This feature is in Preview .