Change In BigQuery Studio, the left pane has been updated with new tab names. The Classic Explorer tab has been renamed to the Data tab, and the Repository tab has been renamed to the Source control tab. The Data tab now includes the Add data button and focuses on data hierarchies. These changes are generally available (GA).
Feature You can now monitor the performance, adoption, latency, and costs of your data agents and their conversations by using Google Cloud Observability in BigQuery. This feature is generally available (GA). Feature The Data Engineering Agent now supports BigQuery AI, ML, and object functions and statements in generated Dataform SQLX pipelines and agent instruction files. This feature is generall…
Feature You can now retrieve query results directly in the Apache Arrow format for faster retrieval speed and improved serialization efficiency. This feature is in Preview.
Feature The Data Engineering Agent now integrates with Google Drive, letting you provide Google Sheets files, CSV, or JSONL files as input for your data engineering pipelines. This feature is generally available (GA).
Feature Python user-defined functions now support volume mounts, which let you access dependency files from Cloud Storage directly from your Python UDF code. This feature is in Preview.
Feature The AI.TRANSLATE function lets you translate text strings between languages. AI.TRANSLATE supports standard Neural Machine Translation (NMT) workloads and Translation LLM (TLLM) capabilities. This function is generally available (GA).
Feature The AI.CHUNK_DOCUMENT function is a table-valued function that splits unstructured documents into semantically coherent text chunks optimized for vector embeddings and Retrieval-Augmented Generation (RAG) workflows. This function is generally available (GA).
Feature Conversational analytics in BigQuery is now available in the following locations: northamerica-northeast1 (Montréal) northamerica-northeast2 (Toronto) For more information, see Locations.
Feature You can copy tables across regions. This feature is now generally available (GA). Feature You can now use column aliases in GoogleSQL. This feature lets you define an alias for an expression in the SELECT clause of a SQL query and immediately reference that alias within the same SELECT list or in the WHERE clause of the same query block. Column aliases also streamline the migration of work…
Feature You can publish a BigQuery Conversational Analytics agent in Gemini Enterprise. This feature is now generally available (GA). Feature The AI.AGG function now supports the output_schema argument, which lets you specify the schema of the function output as a comma-separated list of fields. This feature is generally available (GA).
Feature The AI.AGG function is generally available (GA). You can use this function to semantically aggregate unstructured input data based on natural language instructions.
Feature Incremental data transfers for the BigQuery Data Transfer Service for PostgreSQL and ServiceNow are now generally available (GA).
Feature The BigQuery Data Engineering Agent is now available in the asia-northeast1 (Tokyo) regional endpoint and supports the gemini-3.5-flash model. For more information, see Where Gemini in BigQuery processes your data. This feature is Generally Available (GA).
Feature You can use Gemini assistance in the BigQuery Studio SQL editor through an inline action button when you select text. For more information, see Write SQL with Gemini assistance. This feature is generally available (GA).
Feature BigQuery offers TimesFM 3.0, a built-in time series forecasting model that implements Google Research's open source TimesFM model. You can use TimesFM 3.0 with the following functions: Use AI.FORECAST to perform time series forecasting. In addition to univariate forecasting, you can now perform multivariate forecasting that predicts values for multiple time series based on historical value…
Feature Conversational analytics in BigQuery now supports the AI.CAUSAL_EFFECT function to quantify the impact of specific interventions on time series data. This feature is in Preview.
Feature Iceberg external tables and Iceberg managed tables now support flexible column names by default. This feature is generally available (GA). Feature The gemini-embedding-2 model works well for embedding long strings, including multilingual and unstructured data. It supports a mix of text, images, audio, video, and PDF files. You can use this model in the AI.EMBED, AI.SIMILARITY, and AI.GENER…
Feature The Rust SDK for BigQuery is now generally available (GA). Feature The Data Engineering Agent now supports the gemini-3.7-flash model for the us, eu, and global multi-regional endpoints.
Feature BigQuery pipelines provides support for automated metadata enrichment and Knowledge Catalog data quality scorecard integration. In addition, the Data Engineering Agent can proactively generate semantic metadata for your pipeline assets. For more information, see Metadata enrichment and data quality scorecard integration. These features are generally available.
Feature The BigQuery Security center is now available in the Google Cloud console. You can use the Security center to analyze your data security profile, create and manage row- and column-level security policies, and configure and manage data governance and policy tags. This feature is generally available (GA). Feature You can now view the UPDATE, DELETE, MERGE, and EXPORT execution steps in your…
Feature You can query the INFORMATION_SCHEMA.FAILOVER_HISTORY view to retrieve a near real-time list of failover events for reservations within an administration project that use managed disaster recovery. This feature is now in (Preview).
Feature The BigQuery Data Transfer Service MCP server is now Generally Available (GA). Feature You can now write the output rows produced by BigQuery continuous queries directly into Apache Iceberg managed tables. This lets you continuously process streaming data from BigQuery and write it into your open-format lakehouse by using an INSERT DML statement.
Feature In the BigQuery Studio query editor, the Query results table now keeps the row numbers visible on the left as you scroll horizontally. This helps you maintain context and track data across wide tables. This feature is generally available (GA).
Feature 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 creden…
Feature BigQuery generative AI functions now support the gemini-3.8-flash Gemini model.
Feature You can add unit tests to pipelines to validate your SQL transformation logic against mock datasets. Unit tests for pipelines are generally available (GA).
Feature 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.
Feature Metadata for BigQuery Graph is automatically ingested and searchable in Knowledge Catalog. This feature is available in preview.
Feature 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).
Feature BigQuery generative AI functions now support the following Gemini models: gemini-3.5-flash-lite gemini-3.6-flash gemini-3.7-flash