BigQuery release notes

You can now publish a BigQuery data agent in Gemini Enterprise by registering the agent with Agent Registry and importing it using default Google-managed credentials. When BigQuery and Gemini Enterprise are in the same Google Cloud project and configured with a matching Agent Gateway region, you don't need to manually copy the Agent-to-Agent (A2A) JSON card or configure OAuth client credentials.

These features are in Preview.

The Query results pane in the BigQuery Studio query editor lets you view a short history of recent runs for a query, including multi-statement queries, without having to navigate to the Job history tab. This feature is generally available (GA).

BigQuery generative AI functions now support the gemini-3.8-flash Gemini model.

You can add unit tests to pipelines to validate your SQL transformation logic against mock datasets. Unit tests for pipelines are generally available (GA).

You can use the migration lineage service to visualize the data flow and connections in your source database and help you plan a BigQuery data warehouse migration. This feature is in Preview.

An updated version of the Simba ODBC driver for BigQuery is now available.

Metadata for BigQuery Graph is automatically ingested and searchable in Knowledge Catalog. This feature is available in preview.

You can now include a WHERE clause inside of an aggregate function call to filter your aggregate function input using a boolean expression. This feature is in Preview.

Conversational analytics in BigQuery now supports the ML.CORRELATION function to calculate statistical correlations between a target column and one or more metric columns in a table. This feature is in Preview.

You can now use the ML.METRICS function to compute evaluation metrics for machine learning classification or regression tasks on any table or query that contains actual and predicted values. This function lets you evaluate predictions without needing to create or reference a stored model. This feature is in Preview.

You can use the AI.CAUSAL_EFFECT function to quantify the impact of specific interventions on time series data. This feature is in Preview.

The Data Engineering Agent now integrates with BigQuery Graph to provide additional context between your data source and destination schema, and improves schema mapping accuracy for your data engineering pipelines.

This feature is generally available (GA).

BigQuery generative AI functions now support the following Gemini models:

• gemini-3.5-flash-lite
• gemini-3.6-flash
• gemini-3.7-flash

Conversational analytics now supports predictive modeling questions using the AI.PREDICT function. This feature is in Preview.

Conversational analytics now supports questions about market basket analysis. This feature is generally available (GA).

An updated version of the Simba JDBC driver for BigQuery is now available.

The Rust SDK for BigQuery is now in Preview.

You can now create, store, and manage pipelines in Git folders. This feature is in Preview.

BigQuery now supports TabFM, Google's pre-trained foundation model for tabular data. TabFM enables zero-shot regression and classification through in-context learning. It delivers high-accuracy predictions on structured data without requiring model training or hyperparameter tuning. You can use TabFM directly through the AI.PREDICT function and evaluate model performance by using the AI.EVALUATE function. This feature is in Preview.

Support for configuring daily token quotas for BigQuery generative AI functions has been restored.

Using folders to create, store, and manage pipelines is generally available.

You can now create an identity column, sometimes referred to as an auto-incrementing column, on a table. You can use identity columns to create and maintain primary keys on your tables. When you insert a row into a table that has an identity column, BigQuery generates a unique integer value for that column. This feature is in Preview.

BigQuery Graph is generally available (GA).

BigQuery Graph now includes support for the CALL graph query statement, and the following path inspection GQL functions:

• IS_ACYCLIC
• IS_SIMPLE
• IS_TRAIL.

The Data Engineering Agent is now HIPAA compliant. For more information, see HIPAA compliance on Google Cloud.

Core graph processing for