Table Explorer behavior is moving to the Reference panel. This transition will occur in July 2026 or later. For more information, see Table Explorer.
]]>Use Gemini Cloud Assist to analyze your SQL queries and receive recommendations to optimize query performance in BigQuery. This feature is available to customers who use BigQuery editions. This feature is in Preview.
Support for configuring daily token quotas for BigQuery generative AI functions has been temporarily disabled. We are working to restore this feature as soon as possible.
You can resize the width of table columns in BigQuery Studio for BigQuery listings such as datasets, repositories, job history, and connections. To resize a column, hover over the column divider and drag it to your preferred width.
You can use Gemini Code Assist directly within the BigQuery Jobs explorer, Job details, Job history, and Capacity management pages to help you troubleshoot and analyze performance issues. For more information, see Troubleshoot job performance. This feature is in Preview.
]]>BigQuery AI functions can use
ObjectRef values directly as input,
without calling the OBJ.GET_ACCESS_URL function.
This feature is
generally available
(GA).
You can monitor performance, analyze capacity, and optimize costs with Gemini Cloud Assist in BigQuery. This feature is in Preview.
Support for the
AI.KEY_DRIVERS function
is restored. You can use the
AI.KEY_DRIVERS function to identify segments of data that cause statistically significant changes to a summable metric.
This feature is in Preview.
]]>BigQuery continuous queries now support the following aggregation functions:
Support for these functions is in Preview.
]]>You can analyze data lineage with Gemini Cloud Assist in BigQuery. This feature is in Preview.
You can now use Gemini Cloud Assist to schedule queries. This feature is in Preview.
You can use the Google-developed, open source Java Database Connectivity (JDBC) driver for BigQuery to connect your Java applications to BigQuery. This feature is generally available (GA).
You can use custom constraints with Organization Policy to provide more granular control over specific fields for some BigQuery sharing resources. For more information, see Manage Sharing data exchanges and listings using custom constraints. This feature is generally available (GA).
IAM deny policies for BigQuery are now generally available (GA).
You can manage and limit the costs associated with BigQuery generative AI functions by configuring daily token quotas. Token-based cost management for BigQuery generative AI functions is generally available (GA).
]]>BigQuery fluid scaling, which provides per-second billing with no minimum duration for autoscaling reservations, is generally available (GA).
]]>Remote functions now support a custom path in the endpoint URL. You can reuse a single Cloud Run service for multiple BigQuery remote functions by specifying different path suffixes on the same endpoint. This feature is generally available (GA).
]]>The Facebook Ads connector for the BigQuery Data Transfer Service now supports data transfers from the following Facebook Ads reports:
AdInsightsMMMAdsAdCreativesAdSetsCampaignsAdImagesAdLabelsBusinessesCustomAudiencesAn updated version of the Simba ODBC driver for BigQuery is now available.
]]>The Data Science Agent (DSA) for Colab Enterprise and BigQuery is now generally available (GA).
]]>BigQuery can re-execute instructions (queries) to try to proactively detect performance, correctness, or functional regressions.
These re-executions will have no side effects and will happen with no additional cost or resource consumption.
Data access logs may show bigquery-adminbot@system.gserviceaccount.com when BigQuery re-executes an instruction.
Python UDFs are now Generally Available (GA).
You can use Python UDFs to implement a scalar function in Python and use it in a SQL query. Python UDFs let you install third-party libraries from the Python Package Index (PyPI) and let you access external services using a Cloud resource connection.
You can now use the
AI.AGG function
to semantically aggregate unstructured input data based on natural language
instructions. This feature is in
Preview.
You can group reservations together to prioritize idle slot sharing within the group. Reservations within a reservation group share idle slots with each other before making them available to other reservations in the project, giving you more control over slot allocation for high-priority workloads. This feature is generally available (GA).
You can now use a custom organization policy to allow or deny specific operations on workload management resources including reservations, assignments, capacity commitments, and BI reservations. This feature is in Preview.
You can manage and version control SQL scripts and notebooks with BigQuery Studio Git repositories, which provide a streamlined, folder-based integration with remote Git repositories. This feature is in preview.
]]>The
AI.DETECT_ANOMALIES function
supports calling the function with a single input table that holds both the
historical and target data. This feature is
generally available
(GA).
Support for the AI.KEY_DRIVERS function
preview
has been temporarily disabled. We are working to restore this feature as soon as
possible.
You can now use the
AI.COUNT_TOKENS function
to estimate the token count of text input that you provide. For some generative
AI functions, you can view
the total number of input, output, thought, and cache tokens for each modality
processed by the query. These features are in
Preview.
Starting August 11, 2026, the billing label for the BigQuery Data Transfer
Service SKU will be updated from goog-bq-feature-type: DATA_TRANSFER_SERVICE
(uppercase) to goog-bq-feature-type: data_transfer_service (lowercase) to
provide a more unified and complete view of your costs. This update expands the
scope of the label to cover all costs associated with the BigQuery Data Transfer
Service, including data transfer orchestration, data load operations, and data
merge operations.
To ensure uninterrupted cost visibility, update your billing exports, dashboards, and reporting queries to include both these labels.
]]>You can configure BigQuery sharing listings for multiple regions, which allows you to share datasets and linked replicas across global geographies simultaneously. For more information, see Create a listing. This feature is generally available (GA).
Starting June 1, 2026, due to changes in Google Ads data retention policies, the BigQuery Data Transfer Service connectors for Google Ads, Search Ads 360, and Google Analytics 4 will stop populating data for backfill runs with dates earlier than 37 months from the current date.
For more information about the changes to the Google Ads data retention policies, see New Data Retention Policy for Google Ads starting June 1, 2026.
]]>Starting May 7, 2026, new transfer configurations that transfer data from Google Ads using the BigQuery Data Transfer Service will require Multi-factor authentication (MFA) for individual user authentication. For more information, see May 7, 2026.
]]>Strict act-as mode is enforced globally for all Dataform repositories, requiring the use of a custom service account or user credentials for running Dataform workflows, BigQuery pipelines, notebooks, and data preparations.
You can now use the
VECTOR_INDEX.STATISTICS function to calculate how much an indexed table's data has drifted between when a
vector index was created and the present. If table data has changed enough
to require a vector index rebuild, you can use the
ALTER VECTOR INDEX REBUILD statement
to rebuild the vector index without downtime. These features are
generally available
(GA).
You can now use the PARTITION BY clause of the
CREATE VECTOR INDEX statement
to partition TreeAH vector indexes.
Partitioning enables partition pruning and can decrease I/O costs. This feature
is Generally Available.
You can now create materialized views over active change data capture (CDC) enabled tables. This feature is generally available (GA).
]]>An updated version of the Simba JDBC driver for BigQuery is now available.
]]>You can now use the visual graph modeler in BigQuery Studio to define BigQuery graph nodes and edges from your BigQuery tables and edit graph schema. This feature is available in Preview.
Dataproc is now called Managed Service for Apache Spark. The names for associated API, client library, CLI, and Identity and Access Management (IAM) resources remain unchanged.
BigLake is now called Google Cloud Lakehouse. BigLake metastore is now called the Lakehouse runtime catalog. The names for associated APIs, client libraries, CLI commands, and Identity and Access Management (IAM) remain unchanged and still reference BigLake.
Dataplex Universal Catalog is now called Knowledge Catalog. The API, client library, CLI, and Identity and Access Management (IAM) names remain unchanged. For more information, see Knowledge Catalog overview.
Looker Studio is now called Data Studio.
The website and endpoint change from lookerstudio.google.com to
datastudio.google.com. You do not need to update your reports for this change,
as Data Studio automatically redirects to the new domain. However,
if your company uses proxies to restrict access to external sites, your IT
administrator needs to add the new domain to your access control list (ACL).
The names for associated API, client library, CLI, and Identity and Access
Management (IAM) resources remain unchanged. For more information, see Data Studio returns as new home for Data Cloud
assets.
BigQuery graphs now support the following features:
GRAPH_EXPAND TVF,
and then query measures in that table with the
AGG function.These features are in Preview.
You can now use the Data Engineering Agent to build, modify, and troubleshoot data pipelines in BigQuery. This feature is generally available (GA).
You can now use the gemini-embedding-2-preview model in the
AI.EMBED,
AI.SIMILARITY,
and
AI.GENERATE_EMBEDDING
functions to generate a single embedding from a combination of input types,
including text, image, audio, video, and PDF files.
This feature is in Preview.
You can now visualize BigQuery graph query results and graph schemas directly in BigQuery Studio, without the need of a notebook environment. This feature is in Preview.
]]>Starting July 25, 2026, the BigQuery Data Transfer Service for Facebook Ads
connector will update the data type
mapping for the ActionValue field in the AdInsightsActions report from INT
to FLOAT.
The following features have been added to Python UDFs during Preview:
RecordBatch interface for improved performance.container_request_concurrency, is available for the CREATE FUNCTION
statement. This option controls the maximum number of concurrent requests
per Python UDF container instance.external_service_costs column in the INFORMATION_SCHEMA.JOBS view and in
the ExternalServiceCosts field in the Job API.You can now migrate metadata from external data catalogs to BigLake tables for Apache Iceberg. This feature supports external data catalogs such as such as Apache Hive Metastore and Apache Iceberg REST Catalog. This feature is in Preview.
You can use the BigQuery MCP server to perform a range of data-related tasks with your AI applications including:
This feature is Generally Available (GA).
You can now publish a BigQuery Conversational Analytics agent in Gemini Enterprise. This feature is in Preview.
You can now use the notebook gallery in the BigQuery web UI as your central hub for discovering and using prebuilt notebook templates. This feature is generally available (GA).
]]>Using folders to organize and control access to single file code assets is generally available (GA). In addition, you can perform bulk move and delete operations, refresh folder contents, and view full breadcrumb paths based on resource permissions. For more information, see Create and manage folders.
]]>Conversational analytics now supports querying Lakehouse tables that connect to the Apache Iceberg REST catalog or are federated to an external catalog. For more information, see Query BigLake data with natural language.
This feature is in Preview.
You can now use Colab Data Apps to transform your data analyses from Colab notebooks into polished, interactive applications.
This feature is in Preview.
You can now use the
AI.KEY_DRIVERS function
to identify segments of data that cause statistically significant changes to a
summable metric.
This feature is in Preview.
]]>BigQuery Apache Iceberg external tables now support Iceberg version 3, including binary deletion vectors. For more information, see Apache Iceberg external tables. This feature is in Preview.
A known issue has been resolved where a materialized view refresh could expose masked or filtered data from fine grained access control policies in error messages. No further action is needed.
BigQuery agent analytics is now generally available (GA) in the Google Agent Developer Kit. BigQuery agent analytics is an open source solution that lets you capture, analyze, and visualize multimodal agent interaction data at scale.
You can now use EXPORT DATA
statements to reverse
ETL BigQuery data to AlloyDB. This feature is
in Preview.
Support for the AI.AGG function preview
has been temporarily disabled. We are working to restore this feature as soon as
possible.
To reduce LLM token consumption and query latency when processing large datasets, enable optimized mode using the following managed AI functions:
This feature is in Preview.
The following managed AI functions use Gemini to help you filter, join, rank, and classify your data:
AI.IF:
Filter and join text and unstructured data (such as images, PDFs, audio, or
video) based on a condition described in natural language.AI.SCORE:
Rate text and unstructured data (such as images, PDFs, audio, or video) to
rank your data by quality, similarity, or other criteria.AI.CLASSIFY:
Classify text and unstructured data (such as images, PDFs, audio, or video)
into user-defined categories.These functions are generally available (GA).
You can use visualization cells to automatically generate a visualization of any DataFrame in your notebook. You can customize the columns, chart type, aggregations, colors, labels, and title.
This feature is generally available (GA).
]]>SQL cells in BigQuery notebooks are now generally available (GA).
]]>