This page documents production updates to BigQuery. We recommend that BigQuery developers periodically check this list for any new announcements. BigQuery automatically updates to the latest release and cannot be downgraded to a previous version.
For older release notes, see the Release notes archive.
You can see the latest product updates for all of Google Cloud on the Google Cloud page, browse and filter all release notes in the Google Cloud console, or programmatically access release notes in BigQuery.
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November 11, 2025
You can now use the interactive SQL translator, the translation API, and the batch SQL translator to translate the following SQL dialects into GoogleSQL:
- Apache Impala SQL
- GoogleSQL (BigQuery)
These features are in Preview.
November 10, 2025
You can aggregate and deduplicate table data with Gemini assistance in your BigQuery data preparations. These features are generally available (GA).
Partitioning is now available for BigLake tables for Apache Iceberg in BigQuery. This feature is in Preview.
BigQuery ML now supports the TimesFM 2.5
time series foundational model.
You can use the TimesFM 2.5 model in the
AI.FORECAST,
AI.EVALUATE,
and
AI.DETECT_ANOMALIES
functions to achieve better forecasting accuracy and lower latency.
BigQuery ML now offers the
AI.DETECT_ANOMALIES function.
Use the AI.DETECT_ANOMALIES function with a TimesFM model to
detect anomalies
in time series data, using historical data as a baseline.
This feature is in
Preview.
November 06, 2025
The research paper ARIMA_PLUS: Large-scale, Accurate, Automatic and
Interpretable In-Database Time Series Forecasting and Anomaly Detection in
Google BigQuery is now publicly available.
This paper describes the algorithms behind the
ARIMA_PLUS
and
ARIMA_PLUS_XREG
models for time series forecasting and anomaly detection, and demonstrates the
high performance, scalability, explainability, and customizability of the
models.
November 05, 2025
You can use the
MATCH_RECOGNIZE clause
in your SQL queries to filter and aggregate matches across rows in a table.
This feature is
generally available
(GA).
The BigQuery Data Transfer Service for Google Ads now supports Google Ads API v21.
You can now generate data insights when you
create a
DataScan
using the Dataplex API. This feature is
generally available
(GA).
You can now generate table and column descriptions in all supported Gemini languages when you generate data insights. This feature is generally available (GA).
November 04, 2025
You can now use custom organization policies with the BigQuery migration service to allow or deny specific operations during a BigQuery migration to meet your organization's compliance and security requirements. This includes an option to disable AI suggestions during a migration. This feature is in Preview.
October 31, 2025
We have increased the row capacity for pivot tables backed by BigQuery in Connected Sheets from 100,000 to 200,000 rows.
October 30, 2025
The Apache Iceberg REST catalog in BigLake metastore is now generally available (GA) with several new features, including BigQuery catalog federation, credential vending, and catalog management in the Google Cloud console.
October 29, 2025
You can now 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 in Preview.
October 28, 2025
The BigQuery Data Transfer Service can now transfer data from the following data sources:
Transfers from these data sources are now generally available (GA).
Subscriber email logging lets you log the principal identifiers of users
who execute jobs and queries against linked datasets. You can enable
logging at the
listing level
and the
data exchange level.
The logged data is available in the job_principal_subject field of the
INFORMATION_SCHEMA.SHARED_DATASET_USAGE view.
This feature is
generally available.
October 27, 2025
The administrative jobs explorer now includes a job details page to help you diagnose and troubleshoot queries. The Performance tab compiles query information including the execution graph, SQL text, execution history, performance variance, and system load during execution. You can also compare two jobs to identify discrepancies and potential areas to improve query performance.
This feature is in Preview.
BigQuery now offers the following managed AI functions that use Gemini to help you filter, join, rank, and classify your data:
AI.IF: Filter and join text or multimodal data based on a condition described in natural language.AI.SCORE: Rate text or multimodal input to rank your data by quality, similarity, or other criteria.AI.CLASSIFY: Classify text into user-defined categories.
These functions are in Preview.
You can now use the Data Engineering Agent to use Gemini in BigQuery to build and modify data pipelines to ingest data into BigQuery. This feature is in preview.
You can now use the Apache Arrow format to stream data to BigQuery with the Storage Write API. This feature is generally available (GA).
October 23, 2025
BigQuery is now offering early access to conversational analytics. Conversational analytics accelerates data analysis by enabling quick insights through natural language. Users can chat with their BigQuery data, create custom agents, and access those agents even outside of BigQuery. To enroll in conversational analytics early access, fill out the request form.
October 22, 2025
You can now 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 in preview.
Support for table parameters in table-value functions (TVFs) has been temporarily disabled. We are working to restore this feature as soon as possible.
BigQuery ML now offers a built-in TimesFM univariate time series forecasting model that implements Google Research's open source TimesFM model. You can use BigQuery ML's built-in TimesFM model with the following functions:
- Use
AI.FORECASTto perform forecasting. This function now supports a larger context window. - Use
AI.EVALUATEto evaluate forecasted data against a reference time series based on historical data.
To try using a TimesFM model with the AI.FORECAST function, see
Forecast a time series with a TimesFM univariate model.
This feature is generally available (GA).
October 21, 2025
BigQuery now supports TransUnion for entity resolution. This feature is generally available (GA).
October 20, 2025
You can now 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 in Preview.
In BigQuery ML, you can now fully manage open models as Vertex AI endpoints. BigQuery-managed open models offer the following benefits:
- Manage Vertex AI resource by using SQL queries
- Automatic or immediate open model undeployment to save costs
- Customize model deployment machine types or reserve open model resources by using Compute Engine reservations
This feature is in Preview.
October 16, 2025
The following features are now generally available (GA) in BigQuery Studio:
To streamline resource discovery and access, the left Explorer pane has been reorganized into three sections: Explorer, Classic Explorer, and Git repository. You can still use the Classic Explorer, which provides the complete resources tree.
In the Explorer pane, you can use the search feature to find BigQuery resources in your organization. The results appear in a new tab in the details pane. You can use filters to narrow your search.
You can access job histories by clicking Job history in the Explorer pane. A new tab opens that displays a list of job histories. BigQuery Studio no longer has a bottom pane for job history.
To reduce tab proliferation, clicking a resource opens it within the same tab. To open the resource in a separate tab, press Ctrl (or Command on macOS) and click the resource. To prevent the current tab from getting its content replaced, double-click the tab. The name changes from italicized to regular font. If you still lose your resource, you can click tab_recent Recent tabs in the details pane to find the resource.
You can use breadcrumbs to navigate through different tabs and resources in the details pane.
In the Home tab, the What's new section contains a list of new capabilities and changes to the BigQuery Studio.
The notebook action bar is consolidated by default to give you more screen space for writing code.
You can now access repositories by clicking Repositories in the Explorer pane. A new tab opens that displays a list of repositories. The Explorer pane no longer has a bottom pane for repositories. When you open a workspace in a repository, it opens in the Git repository pane in the left pane. These features are available in BigQuery Studio in preview.
October 15, 2025
You can visualize your geospatial query results on an interactive map in BigQuery Studio. This feature is generally available (GA).
You can use the dbt-bigquery adapter to run Python code that's defined in
BigQuery DataFrames. For more information, see
Use BigQuery DataFrames in dbt.
This feature is
generally available
(GA).
October 14, 2025
The BigQuery Data Transfer API (bigquerydatatransfer.googleapis.com) is now enabled by default for every new Google Cloud project. This feature is generally available (GA).
You can now embed natural language as comments in existing SQL to refine and transform your code. This feature is preview.
October 09, 2025
An updated version of the ODBC driver for BigQuery is now available.
You can allocate idle slots fairly across reservations within a single admin project. This ensures each reservation receives an approximately equal share of available capacity. This feature is now generally available (GA).
You can set a maximum slot limit for a reservation. You can configure the maximum reservation size when creating or updating a reservation. This feature is now generally available (GA).
Security, privacy, and compliance for Gemini in BigQuery details how customer data is protected and processed by Gemini in BigQuery.
October 08, 2025
The default limit of QueryUsagePerDay for
on-demand pricing has changed. The default limit of all new projects is now 200
TiB. For existing projects, the default limit has been set based on your
project's usage over the last 30 days. Projects that have custom cost
controls configured or that use
reservations aren't affected.
If the new limit might affect your workload, create a custom cost
control based on your workload needs.
You can set labels on reservations. These labels can be used to organize your reservations and for billing analysis. This feature is generally available (GA).
You can specify which reservation a query uses at runtime, and set IAM policies directly on reservations. This provides more flexibility and fine-grained control over resource management. This feature is generally available (GA).
October 07, 2025
As of February 25, 2025, enhancements to the workload management autoscaler that were announced on July 31, 2024 have rolled out to all users. These enhancements are generally available (GA).
October 06, 2025
The INFORMATION_SCHEMA.SHARED_DATASET_USAGE view
now includes the following schema fields to support usage metrics for
external tables and routines:
shared_resource_id: the ID of the queried resourceshared_resource_type: the type of the queried resourcereferenced_tables: Containsproject_id,dataset_id,table_id, andprocessed_bytesfields of the base table.
These fields are generally available (GA).
The BigQuery Data Transfer Service can now transfer reporting data from Google Analytics 4 into BigQuery. You can also include custom reports from Google Analytics 4 in your data transfer. This feature is generally available (GA).
You can now set the priority of BigQuery jobs initiated by Dataform workflows to run queries as interactive jobs that start running as quickly as possible or as batch jobs with lower priority. For more information, see Create a pipeline schedule and InvocationConfig. This feature is generally available (GA).
Starting March 17, 2026, the BigQuery Data Transfer Service will require the
bigquery.datasets.setIamPolicy and the bigquery.datasets.getIamPolicy
permissions on the target dataset to create or update a transfer configuration.
For more information, see Changes to dataset-level access controls.
October 02, 2025
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 in preview.
October 01, 2025
You can now apply SQL query generated in the Gemini Cloud Assist chat to the query open in your editor. This feature is in Preview.
September 29, 2025
To simplify access management for your Iceberg tables, you can use credential vending mode with the Apache Iceberg REST catalog in BigLake metastore. Credential vending removes the need for catalog users to have direct access to Cloud Storage buckets. This feature is in Preview.
You can now create BigQuery non-incremental materialized views over Spanner data to improve query performance by periodically caching results. This feature is in Preview.
BigQuery data preparation supports unnesting arrays, which expands each array element into its own row for easier analysis. For more information, see Unnest arrays. This feature is generally available (GA).
History-based query optimizations are now enabled by default. If history-based optimizations have been previously disabled, you can re-enable history-based optimizations for your project or organization.
September 25, 2025
The
ARRAY_FIRST,
ARRAY_LAST,
and
ARRAY_SLICE
GoogleSQL functions are now
generally available (GA).
BigQuery data canvas now supports destination table nodes. Destination table nodes let you persist query results to a new or existing table. This feature is generally available (GA).
September 24, 2025
BigQuery ML now supports
visualization of model monitoring metrics.
This feature lets you use charts and graphs to
analyze model monitoring function output.
You can use metric visualization with the
ML.VALIDATE_DATA_SKEW
and
ML.VALIDATE_DATA_DRIFT
functions. This feature is
generally available
(GA).
For command-line users, BigQuery is now integrated with the Gemini CLI to provide an agentic CLI experience. Using the dedicated Gemini CLI extensions for BigQuery, you can search, explore, analyze, and gain insights from your data by asking natural language questions, generating forecasts, and running contribution analysis directly from the command line. This feature is available in beta.
September 22, 2025
You can now run federated queries against PostgreSQL dialect databases in Spanner using BigQuery external datasets with GoogleSQL; this includes cross-region federated queries. This feature is generally available (GA).
September 16, 2025
You can now access snapshots of Apache Iceberg external tables that are retained in your Iceberg metadata by using the FOR SYSTEM_TIME AS OF clause. This feature is generally available (GA).
You can use the JSON_KEYS function to extract unique JSON keys from a JSON expression, and you can specify a mode for some JSON functions that take a JSONPath to allow more flexibility in how the path matches the JSON structure. These features are generally available (GA).
SQL code completion is now available for all BigQuery projects. To learn how to enable and activate Gemini in BigQuery features, see Set up Gemini in BigQuery. This feature is available in preview.
September 15, 2025
In the BigQuery Studio, in the Explorer pane, you can now open saved queries in Connected Sheets. This feature is generally available (GA).
You can now enable the BigQuery advanced runtime to improve query execution time and slot usage. This feature is generally available (GA). Between September 15, 2025 and early 2026, the BigQuery advanced runtime will become the default runtime for all projects.
Java
2.55.0 (2025-09-12)
Features
Dependencies
Python
3.37.0 (2025-09-08)
Features
Bug Fixes
Documentation
September 11, 2025
Use the BigQuery migration assessment for Informatica to assess the complexity of migrating data from your Informatica platform to BigQuery. This feature is in Preview.
Gemini now recommends natural language prompts for you in the SQL generation tool. This feature is in Preview.
When you use the Data Science Agent in BigQuery, you can now use the Apache Spark or PySpark keywords in your prompt. The Data Science Agent is in Preview.
September 10, 2025
You can load files from Cloud Storage in BigQuery data preparations. This feature is in Preview.
September 09, 2025
The batch and interactive translators now caches your metadata, which can improve latency when you run a SQL translation. This feature is generally available (GA).
You can now perform supervised tuning on a BigQuery ML remote model based on a Vertex AI gemini-2.5-pro or gemini-2.5-flash-lite model.
You can configure reusable, default Cloud resource connections in a project. Default connections are generally available (GA).
September 08, 2025
You can now add tables and views as tasks to BigQuery pipelines. For more information, see Add a pipeline task. This feature is in Preview.
When you use the Data Science Agent in BigQuery, you can now use the @ symbol to search for BigQuery tables in your project, and you can use the + symbol to search for files to upload. The Data Science Agent is in Preview.
You can now include table parameters when you create a table-valued function (TVF). This feature is in Preview.
September 03, 2025
BigQuery now supports soft failover with managed disaster recovery. This feature is generally available (GA).
You can flatten records in BigQuery data preparation with a single operation. This feature is generally available (GA).
The INFORMATION_SCHEMA.RESERVATIONS_TIMELINE view now includes the per_second_details schema field. This new field provides information regarding reservation capacity and usage on a per-second basis, and also includes details on autoscale utilization. This feature is generally available (GA).
September 02, 2025
You can now create a remote model based on an open embedding model from Vertex Model Garden or Hugging Face that is deployed to Vertex AI. Options include E5 Embedding and other leading open embedding generation models. You can then use the ML.GENERATE_EMBEDDING function with this remote model to generate embeddings.
Try this feature with the Generate text embeddings by using an open model and the ML.GENERATE_EMBEDDING function tutorial.
This feature is in Preview.
You can now create a remote model based on the Vertex AI gemini-embedding-001 model. You can then use the ML.GENERATE_EMBEDDING function with this remote model to generate embeddings. This feature is in Preview.
You can now reference BigQuery ML and DataFrames in your prompts when you use the Data Science Agent in a BigQuery notebook. The Data Science Agent is in Preview.
You can now enable the automatic selection of a processing location in your pipeline configurations. For more information, see Create pipelines. This feature is generally available (GA).
You can now enable the automatic selection of a processing location in your pipeline configurations. For more information, see Create pipelines. This feature is generally available (GA).
September 01, 2025
Go
1.70.0 (2025-08-28)
Features
- bigquery/reservation: Add Reservation.max_slots field to Reservation proto, indicating the total max number of slots this reservation can use up to (f1de706)
- bigquery/reservation: Add Reservation.scaling_mode field and its corresponding enum message ScalingMode. This field should be used together with Reservation.max_slots (f1de706)
- bigquery/storage/managedwriter: Allow overriding proto conversion mapping (#12579) (ce9d29b), refs #12578
- bigquery: Add load/extract job completion ratio (#12471) (3dab483)
- bigquery: Load job and external table opts for custom time format, null markers and source column match (#12470) (67b0320)
August 28, 2025
For additional layers of security and control, you can now use query templates to predefine and limit the queries that can be run in data clean rooms. For more information, see Use query templates. This feature is in preview.
August 26, 2025
You can deduplicate table data with Gemini assistance in your BigQuery data preparations. Deduplication is in Preview.
August 25, 2025
You can use the ST_REGIONSTATS geography function to combine raster data using Earth Engine with your vector data stored in BigQuery. For more information, see Work with raster data and try the tutorial that shows you how to use raster data to analyze global temperature. This feature is generally available.
You can now use data insights to have Gemini generate table and column descriptions from table metadata. This feature is generally available (GA).
August 22, 2025
Multi-statement transactions are now available for BigLake Iceberg tables in BigQuery. This feature is in Preview.
August 21, 2025
Starting September 25, 2025, the BigQuery Data Transfer Service for third-party SAAS and database connectors will update to a consumption-based pricing model. With this new pricing model, you will be charged based on the compute resources consumed by your data transfers, measured in slot-hours. For more information, see Data Transfer Service pricing. This pricing update applies to the following third-party connectors when they are generally available (GA):
- Facebook Ads
- MySQL
- Oracle
- PostgreSQL
- Salesforce
- Salesforce Marketing Cloud
- ServiceNow
- Other third-party connectors planned for future releases
August 18, 2025
In the BigQuery console, you can now use the Reference panel to do the following:
In the query editor, you can use the Reference panel to preview the schema details of tables, snapshots, views, and materialized views, or open these resources in a new tab. You can also use the panel to construct new queries or edit existing queries by inserting query snippets or field names.
In the notebook editor, you can use the Reference panel to preview the schema details of tables, snapshots, views, or materialized views, or open these resources in a new tab.
This feature is generally available (GA).
When you use the Data Science Agent in BigQuery, you can now use the table selector to choose one or more BigQuery tables to analyze. The Data Science Agent is in Preview.
August 14, 2025
You can now visualize your geospatial query results on an interactive map in BigQuery studio. This feature is in preview.
You can use cross region federated queries to query Spanner tables from regions other than the source BigQuery region. These cross region queries incur additional Spanner network egress charges. This feature is generally available (GA).
August 13, 2025
You can aggregate table data with Gemini assistance in your BigQuery data preparations. Aggregations in data preparations are in Preview.
August 12, 2025
You can now save query results to Cloud Storage. This feature is generally available (GA).
August 11, 2025
BigQuery resource utilization charts are generally available (GA).
You can now use WITH expressions in your GoogleSQL queries to create temporary variables. This feature is generally available (GA).
You can now use chained function call syntax in GoogleSQL to make deeply nested function calls easier to read. This feature is generally available (GA).
BigQuery data preparations are now represented in the SQLX format and in the pipe query syntax to simplify the CI/CD code review process. For more information, see Manage data preparations.
August 06, 2025
Enabling the advanced runtime now includes short query optimizations. This feature is in preview.
August 04, 2025
You can now use the new Data Science Agent (DSA) for Colab Enterprise and BigQuery to automate exploratory data analysis, perform machine learning tasks, and deliver insights all within a Colab Enterprise notebook. This feature is in preview.
Java
2.54.0 (2025-07-31)
Features
- bigquery: Add OpenTelemetry Samples (#3899) (e3d9ed9)
- bigquery: Add otel metrics to request headers (#3900) (4071e4c)
Dependencies
- update dependency com.google.cloud:google-cloud-bigquerystorage-bom to v3.16.1 (#3912) (https://github.com/googleapis/java-bigquery/commit/bb6f6dcb90b1ddf72e630c4dc64737cf2c2ebd2e)
- Update dependency com.google.api.grpc:proto-google-cloud-bigqueryconnection-v1 to v2.70.0 (#3890) (84207e2)
- Update dependency com.google.apis:google-api-services-bigquery to v2-rev20250706-2.0.0 (#3910) (ae5c971)
- Update dependency com.google.cloud:sdk-platform-java-config to v3.50.2 (#3901) (8205623)
- Update dependency io.opentelemetry:opentelemetry-api to v1.52.0 (#3902) (772407b)
- Update dependency io.opentelemetry:opentelemetry-bom to v1.52.0 (#3903) (509a6fc)
- Update dependency io.opentelemetry:opentelemetry-context to v1.52.0 (#3904) (96c1bae)
- Update dependency io.opentelemetry:opentelemetry-exporter-logging to v1.52.0 (#3905) (28ee4c9)
July 31, 2025
You can manage data profile scans and data quality scans across your project by using the Metadata curation page in the Google Cloud console. For more information, see Profile your data and Scan for data quality issues. This feature is generally available (GA).
BigQuery ML now can automatically detect model quota increases in Vertex AI, and automatically adjusts the quota for any BigQuery ML functions that use those models. You no longer need to email the BigQuery ML team to increase model quota.
You can now use continuous queries to export BigQuery data to Spanner in real time. This feature is in Preview.
BigQuery ML has improved throughput by more than 100x for the following generative AI functions:
Actual performance varies based on the number of input and output tokens in the request, but a typical 6-hour job can now process millions of rows. For more information, see Generative AI functions.
July 30, 2025
The Gemini for Google Cloud API (cloudaicompanion.googleapis.com) is now enabled by default for most BigQuery projects. Exceptions include projects where customers have opted out, and those linked to accounts based in EMEA regions including BigQuery Europe, Middle East, and Africa regions.
July 28, 2025
You can now associate data policies directly on columns. This feature enables direct database administration for controlling access and applying masking and transformation rules at the column level. This feature is in Preview.
July 22, 2025
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. This feature is in Preview.
Access Transparency supports BigQuery data preparation in the GA stage.
The CREATE EXTERNAL TABLE and LOAD DATA statements now support the following options in Preview:
null_markers: define the strings that representNULLvalues in CSV files.source_column_match: specify how loaded columns are matched to the schema. You can match columns by position or by name.
You can now use the MATCH_RECOGNIZE clause in your SQL queries to filter and aggregate matches across rows in a table. This feature is in Preview.
July 21, 2025
You can now use the DISTINCT pipe operator to select distinct rows from a table in your pipe syntax queries. This feature is generally available (GA).
Java
2.53.0 (2025-07-14)
Features
- bigquery: Add OpenTelemetry support to BQ rpcs (#3860) (e2d23c1)
- bigquery: Add support for custom timezones and timestamps (#3859) (e5467c9)
- Next release from main branch is 2.53.0 (#3879) (c47a062)
Bug Fixes
Dependencies
- Update dependency com.google.api.grpc:proto-google-cloud-bigqueryconnection-v1 to v2.69.0 (#3870) (a7f1007)
- Update dependency com.google.apis:google-api-services-bigquery to v2-rev20250615-2.0.0 (#3872) (f081589)
- Update dependency com.google.cloud:sdk-platform-java-config to v3.50.1 (#3878) (0e971b8)
Documentation
Python
3.35.0 (2025-07-15)
Features
- Add null_markers property to LoadJobConfig and CSVOptions (#2239) (289446d)
- Add total slot ms to RowIterator (#2233) (d44bf02)
- Add UpdateMode to update_dataset (#2204) (eb9c2af)
- Adds dataset_view parameter to get_dataset method (#2198) (28a5750)
- Adds date_format to load job and external config (#2231) (7d31828)
- Adds datetime_format as an option (#2236) (54d3dc6)
- Adds source_column_match and associated tests (#2227) (6d5d236)
- Adds time_format and timestamp_format and associated tests (#2238) (371ad29)
- Adds time_zone to external config and load job (#2229) (b2300d0)
Bug Fixes
- Adds magics.context.project to eliminate issues with unit tests … (#2228) (27ff3a8)
- Fix rows returned when both start_index and page_size are provided (#2181) (45643a2)
- Make AccessEntry equality consistent with from_api_repr (#2218) (4941de4)
- Update type hints for various BigQuery files (#2206) (b863291)
Documentation
July 17, 2025
You can now use the WITH pipe operator to define common table expressions in your pipe syntax queries. This feature is generally available (GA).
You can now use named windows in your pipe syntax queries. This feature is generally available (GA).
July 16, 2025
You can now add comments to notebooks, data canvases, data preparation files, or saved queries. You can also reply to existing comments or get a link to them. This feature is in Preview.
You can now create BigQuery ML models by using the Google Cloud console user interface. This feature is in Preview.
July 15, 2025
You can now commercialize your BigQuery sharing listings on Google Cloud Marketplace. This feature is generally available (GA).
You can flatten JSON columns in BigQuery data preparation with a single operation. This feature is generally available (GA).
July 08, 2025
Starting August 1, 2025, GoogleSQL will become the default dialect for queries run from the command line interface (CLI) or API. To use LegacySQL, you will need to explicitly specify it in your requests or set the configuration setting default_sql_dialect_option to 'default_legacy_sql' at the project or organization level.
July 07, 2025
You can now use your Google Account user credentials to authorize the execution of a data preparation in development. For more information, see Manually run a data preparation in development. This feature is in preview.
July 01, 2025
You can now update a Cloud KMS encryption key by updating the table with the same key. This feature is generally available (GA).
You can use the @@location system variable to set the location in which to run a query. This feature is generally available (GA).
BigQuery now supports the following Apache Hadoop migration features in Preview:
- Use the
dwh-migration-dumpertool to migrate the metadata necessary for a Hadoop permissions and data migration. - Migrate permissions from Apache Hadoop, Apache Hive, and Ranger HDFS to BigQuery.
- Migrate tables from a HDFS data lake to Google Cloud.
June 30, 2025
You can now create and manage scheduled notebooks using the Schedule details pane in BigQuery Studio. This feature is generally available (GA).
Java
2.52.0 (2025-06-25)
Features
- bigquery: Integrate Otel in client lib (#3747) (6e3e07a)
- bigquery: Integrate Otel into retries, jobs, and more (#3842) (4b28c47)
Bug Fixes
Dependencies
- Remove version declaration of open-telemetry-bom (#3855) (6f9f77d)
- Update dependency com.google.api.grpc:proto-google-cloud-bigqueryconnection-v1 to v2.66.0 (#3835) (69be5e7)
- Update dependency com.google.api.grpc:proto-google-cloud-bigqueryconnection-v1 to v2.68.0 (#3858) (d4ca353)
- Update dependency com.google.cloud:sdk-platform-java-config to v3.49.2 (#3853) (cf864df)
- Update dependency com.google.cloud:sdk-platform-java-config to v3.50.0 (#3861) (eb26dee)
- Update dependency io.opentelemetry:opentelemetry-bom to v1.51.0 (#3840) (51321c2)
- Update ossf/scorecard-action action to v2.4.2 (#3810) (414f61d)
June 26, 2025
You can now use the
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 in preview.
BigQuery search indexes provide free index management until your organization reaches the limit in a given region. You can now use the INFORMATION_SCHEMA.SEARCH_INDEXES_BY_ORGANIZATION view to understand your current consumption towards that limit, broken down by projects and tables. This feature is generally available (GA).
June 23, 2025
You can now use the Apache Iceberg REST catalog in BigLake metastore to create interoperability between your query engines by allowing your open source engines to access Iceberg data in Cloud Storage. This feature is in Preview.
Colab Enterprise notebooks in BigQuery let you do the following in Preview:
June 18, 2025
You can now publish the results of a data quality scan as Dataplex Universal Catalog metadata. Previously, data quality scan results were published only to the Google Cloud console. The latest results are saved to the entry that represents the source table. You can view the results in the Google Cloud console. If you want to enable catalog publishing for an existing data quality scan, you must edit the scan and re-enable the publishing option. This feature is generally available (GA).
You can now use data insights to have Gemini generate table and column descriptions from table metadata. This feature is in Preview.
June 16, 2025
In BigQuery ML, you can now forecast multiple time series at once by using the TIME_SERIES_ID_COL option that is available in ARIMA_PLUS_XREG multivariate time series models. Try this feature with the Forecast multiple time series with a multivariate model tutorial. This feature is generally available (GA).
You can now manage IAM tags on BigQuery datasets and tables using SQL. This feature is generally available (GA).
The BigQuery migration assessment is now available for workflows that use Cloudera and Apache Hadoop. This feature is in Preview.
The Merchant Center best sellers report supports multi-client accounts (MCAs). If you have an MCA, you can use the aggregator_id to query the tables. The BestSellersEntityProductMapping table maps the best-selling entities to the products in the sub-accounts' inventory. This provides a consolidated view of best-selling products, which you can then join with product data for more detailed insights. This feature is generally available (GA).
BigQuery now offers the following Gemini-enhanced SQL translation features:
- Create Gemini-based configuration YAML files to generate AI suggestions for batch or interactive SQL translations. This feature is now generally available (GA).
- After making a batch SQL translation, review your translation output, including Gemini-based suggestions, using the code tab and configuration tab. This feature is now generally available (GA).
- When making an interactive SQL translation, create and apply Gemini-enhanced translation rules to customize your SQL inputs. This feature is in Preview.
June 12, 2025
Dark theme is now available for BigQuery in Preview. To enable the dark theme, in the Google Cloud console, click Settings and utilities > Preferences. In the navigation menu, click Appearance, and then select your color theme and click Save.
June 11, 2025
The following GoogleSQL functions are now available in preview:
- The
ARRAY_FIRSTfunction returns the first element of the input array. - The
ARRAY_LASTfunction returns the last element of the input array. - The
ARRAY_SLICEfunction returns an array that contains consecutive elements from the input array.
June 10, 2025
An updated version of the ODBC driver for BigQuery is now available.
For supported Gemini models, you can now use Vertex AI Provisioned Throughput with the ML.GENERATE_TEXTand AI.GENERATE functions to provide consistent high throughput for requests.
This feature is generally available (GA).
June 09, 2025
You can reference Iceberg external tables in materialized views instead of migrating that data to BigQuery-managed storage. This feature is generally available (GA).
Java
2.51.0 (2025-06-06)
Features
- bigquery: Job creation mode GA (#3804) (a21cde8)
- bigquery: Support Fine Grained ACLs for Datasets (#3803) (bebf1c6)
Dependencies
- Rollback netty.version to v4.1.119.Final (#3827) (94c71a0)
- Update dependency com.google.api.grpc:proto-google-cloud-bigqueryconnection-v1 to v2.65.0 (#3787) (0574ecc)
- Update dependency com.google.apis:google-api-services-bigquery to v2-rev20250511-2.0.0 (#3794) (d3bf724)
- Update dependency com.google.cloud:sdk-platform-java-config to v3.49.0 (#3811) (2c5ede4)
June 04, 2025
The organization-level configuration settings for default_sql_dialect_option and query_runtime are unsupported.
June 03, 2025
You can now use the BigQuery advanced runtime to improve query execution time and slot usage. This feature is in Preview.
BigQuery tables for Apache Iceberg have been renamed BigLake tables for Apache Iceberg in BigQuery. This feature is now generally available (GA).
BigQuery metastore has been renamed BigLake metastore and is now generally available (GA). The feature formerly known as BigLake metastore has been renamed BigLake metastore (classic).
June 02, 2025
In the navigation menu, you can now go to Settings and select Configuration settings to customize the BigQuery Studio experience for users within the selected project or organization. This is achieved by showing or hiding user interface elements. This feature is in preview.
BigQuery now supports using Spanner external datasets with authorized views, authorized routines, and Cloud resource connections. This feature is generally available (GA).
The CREATE EXTERNAL TABLE and LOAD DATA statements now support the following options in preview:
time_zone: specify a time zone to use when loading datadate_format,datetime_format,time_format, andtimestamp_format: define how date and time values are formatted in your source files
In the BigQuery console, in the Welcome tab, you can now try the Apache Spark demo notebook that walks you through the basics of Spark notebook and showcases serverless Spark in BigQuery. This feature is generally available (GA).
Go
1.69.0 (2025-05-27)
Features
- bigquery/analyticshub: Add support for Analytics Hub & Marketplace Integration (2aaada3)
- bigquery/analyticshub: Adding allow_only_metadata_sharing to Listing resource (2aaada3)
- bigquery/analyticshub: Adding CommercialInfo message to the Listing and Subscription resources (2aaada3)
- bigquery/analyticshub: Adding delete_commercial and revoke_commercial to DeleteListingRequest and RevokeSubscriptionRequest (2aaada3)
- bigquery/analyticshub: Adding DestinationDataset to the Subscription resource (2aaada3)
- bigquery/analyticshub: Adding routine field to the SharedResource message (2aaada3)
- bigquery: Add support for dataset view and update modes (#12290) (7c1f961)
- bigquery: Job creation mode GA (#12225) (1d8990d)
May 29, 2025
You can now use the dbt-bigquery adapter to run Python code that's defined in BigQuery DataFrames. For more information, see Use BigQuery DataFrames in dbt. This feature is in preview.
You can now use your Google Account user credentials to authorize the creation, scheduling, and running of pipelines as well as the scheduling of notebooks and data preparations. For more information, see Create a pipeline schedule. This feature is in preview.
You can now create event-driven transfers when transferring data from Cloud Storage to BigQuery. Event-driven transfers can automatically trigger transfer runs when data in your Cloud Storage bucket has been modified or added. This feature is generally available (GA).
May 28, 2025
You can now create a serverless Spark session and run PySpark code in a BigQuery notebook. This feature is generally available (GA).
Column metadata indexing is now available for both BigQuery tables and external tables. This feature is generally available (GA).
May 27, 2025
You can now share Pub/Sub streaming data through BigQuery sharing with additional client libraries support and provider usage metrics. This feature is generally available (GA).
BigQuery offers optional job creation mode to speed up small queries that you use in your dashboards, data exploration, and other workflows. This mode automatically optimizes eligible queries and uses a cache to improve latency. This feature is generally available (GA).
May 26, 2025
May 22, 2025
When you migrate Teradata data to BigQuery using the BigQuery Data Transfer Service, you can now specify the outputs of the BigQuery translation engine to use as schema mapping. This feature is in preview.
You can use custom constraints with Organization Policy to provide more granular control over specific fields for some BigQuery resources. This feature is available in Preview.
Starting March 17 2026, the bigquery.datasets.getIamPolicy
IAM permission is required to view a dataset's access controls and to query the
INFORMATION_SCHEMA.OBJECT_PRIVILEGES
view. The bigquery.datasets.setIamPolicy permission is required to update a
dataset's access controls or to create a dataset with access controls using the
API. For more information on this change and how to opt into early enforcement, see Changes to dataset-level access controls.
When you Set up Gemini in BigQuery you are now prompted to grant the BigQuery Studio User and BigQuery Studio Admin roles. These roles now include permission to use Gemini in BigQuery features. This feature is generally available (GA).
You can select multiple columns and perform data preparation tasks on them, including dropping columns. For more information, see Prepare data with Gemini. This feature is generally available (GA).
May 21, 2025
You are now able to set access controls on routines. This feature is in Preview.
You can now perform supervised tuning on a BigQuery ML remote model based on a Vertex AI gemini-2.0-flash-001 or gemini-2.0-flash-lite-001 model.
May 19, 2025
Continuous queries let you build long-lived, continuously processing SQL statements that can analyze, process, and perform machine learning (ML) inference on incoming data in BigQuery in real time.
- To monitor your continuous queries, you can use a custom job ID prefix to simplify filtering or view metrics specific to continuous queries in Cloud Monitoring.
- Continuous queries can use slot autoscaling to dynamically scale allocated capacity to accommodate your workload.
This feature is generally available (GA).
Spanner now supports cross regional federated queries from BigQuery which allow BigQuery users to query Spanner tables from regions other than their BigQuery region. Users don't incur Spanner network egress charges during the preview period. This feature is in preview.
Python
3.32.0 (2025-05-12) - YANKED
Reason this release was yanked:
PR #2154 caused a performance regression.
Features
- Add dataset access policy version attribute (#2169) (b7656b9)
- Add preview support for incremental results (#2145) (22b80bb)
- Add WRITE_TRUNCATE_DATA enum (#2166) (4692747)
- Adds condition class and assoc. unit tests (#2159) (a69d6b7)
- Support BigLakeConfiguration (managed Iceberg tables) (#2162) (a1c8e9a)
- Update the AccessEntry class with a new condition attribute and unit tests (#2163) (7301667)
Bug Fixes
Go
1.68.0 (2025-05-12)
Features
- bigquery/analyticshub: Support new feature Sharing Cloud Pubsub Streams via AH (GA) and Subscriber Email logging feature (#11908) (a21d596)
- bigquery/storage: Increased the number of partitions can be written in a single request (43bc515)
- bigquery: Add performance insights (#12101) (aef68ab)
- bigquery: Add some missing fields to BQ stats (#12212) (77b08e8)
- bigquery: Add WriteTruncateData write disposition (#12013) (b1126a3)
- bigquery: New client(s) (#12228) (f229bd9)
- bigquery: Support managed iceberg tables (#11931) (35e0774)
- bigquery: Support per-job reservation assignment (#12078) (c9cebcc)
Bug Fixes
- bigquery: Cache total rows count (#12230) (202dce0), refs #11874 #11873
- bigquery: Parse timestamps with timezone info (#11950) (530d522)
- bigquery: Update google.golang.org/api to 0.229.0 (3319672)
- bigquery: Upgrade gRPC service registration func (7c01015)
Documentation
- bigquery/storage: Updated the number of partitions (from 100 to 900) can be inserted, updated and deleted in a single request (43bc515)
May 14, 2025
You can now schedule automated data transfers from Snowflake to BigQuery using the BigQuery Data Transfer Service. This feature is in preview.
BigQuery now supports cross-region transfers for batch loading and exporting data. You can load or export your data from any region or multi-region to any other region or multi-region using a single bq load, LOAD DATA, bq extract, or EXPORT DATA statement. This feature is generally available (GA).
Vector indexes support the TreeAH index type, which uses Google's ScaNN algorithm. The TreeAH index is optimized for efficient batch processing, capable of handling anywhere from a few thousand to hundreds of thousands of embeddings at once. This feature is generally available (GA).
May 13, 2025
The following SQL features are now generally available (GA) in BigQuery:
GROUP BY STRUCTand theSELECT DISTINCTclause.GROUP BY ARRAYand theSELECT DISTINCTclause.GROUP BY ALLclause.
May 12, 2025
BigQuery resource utilization charts have the following changes:
- The default timeline shown in the event timeline chart has changed from one to six hours.
- Several improvements have been made to the views, including a new reservation slot usage view. This view helps monitor idle, baseline, and autoscaled slot usage.
This feature is in Preview.
You can now view the Query text section in a BigQuery execution graph to understand how the stage steps are related to the query text. This feature is in preview.
You can now use BigQuery and BigQuery DataFrames to enable multimodal analysis, transformation, and data engineering (ELT) workflows in both SQL and Python. Use multimodal data features to do the following:
Integrate unstructured data into standard tables by using
ObjectRefvalues, and then work with this data in analysis and transformation workflows by usingObjectRefRuntimevalues.Use generative AI to analyze multimodal data and generate embeddings by using BigQuery ML SQL functions or BigQuery DataFrames methods with Gemini and multimodal embedding models.
Create multimodal DataFrames in BigQuery DataFrames, and then use object transformation methods to transform images and chunk PDF files.
Use Python user-defined functions (UDFs) to transform images and chunk PDF files.
This feature is in Preview.
Java
2.50.0 (2025-05-06)
Features
- Add WRITE_TRUNCATE_DATA as an enum value for write disposition (#3752) (acea61c)
- bigquery: Add support for reservation field in jobs. (#3768) (3e97f7c)
Dependencies
- Update dependency com.google.api.grpc:proto-google-cloud-bigqueryconnection-v1 to v2.63.0 (#3770) (934389e)
- Update dependency com.google.apis:google-api-services-bigquery to v2-rev20250404-2.0.0 (#3754) (1381c8f)
- Update dependency com.google.apis:google-api-services-bigquery to v2-rev20250427-2.0.0 (#3773) (c0795fe)
- Update dependency com.google.cloud:sdk-platform-java-config to v3.46.3 (#3772) (ab166b6)
- Update dependency com.google.cloud:sdk-platform-java-config to v3.47.0 (#3779) (b27434b)
May 06, 2025
In the Google Cloud console, Analytics Hub has been renamed BigQuery sharing (Analytics Hub).
May 05, 2025
Changes that you make to your saved queries are now automatically saved. This feature is in preview.
April 28, 2025
When you translate SQL queries from your source database, you can use configuration YAML files to optimize and improve the performance of your translated SQL. This feature is generally available (GA).
Dataplex automatic discovery in BigQuery scans your data in Cloud Storage buckets to extract and catalog metadata, creating BigLake, external, or object tables for analytics and AI for insights, security, and governance. This feature is generally available (GA).
April 24, 2025
You can now work with a Gemini powered assistant in a BigQuery data canvas. The data canvas assistant is an agent-like tool, capable of constructing and modifying a data canvas to answer data analytics questions from user prompting. This feature is now in Preview.
April 23, 2025
You can now set a maximum slot limit for a reservation. You can configure the maximum reservation size when creating or updating a reservation. This feature is in public preview.
You can now specify which reservation a query uses at runtime, and set IAM policies directly on reservations. This provides more flexibility and fine-grained control over resource management. This feature is in public preview.
You can now allocate idle slots fairly across reservations within a single admin project. This ensures each reservation receives an approximately equal share of available capacity. This feature is in public preview.
April 21, 2025
BigQuery now provides spend-based committed use discounts (CUDs). Spend-based committed use discounts provide a discount in exchange for your commitment to spend a minimum amount per hour on PAYG compute resources listed here. You can purchase CUDs with a one or three year commitment period.
You can now enable fine-grained access control on BigQuery metastore Iceberg tables. This feature is generally available (GA).
You can get the required permissions to use BigQuery data preparation through the BigQuery Studio User (roles/bigquery.studioUser) and Gemini for Google Cloud User (roles/cloudaicompanion.user) roles, and permission to access the data you're preparing.
BigQuery data preparation no longer requires that you have the permissions granted by the following IAM roles:
- BigQuery Data Editor (
roles/bigquery.dataEditor) - Service Usage Consumer (
roles/serviceusage.serviceUsageConsumer)
For more information about the required roles, see Manage data preparations.
April 17, 2025
You can now use BigQuery DataFrames version 2.0, which makes security and performance improvements to the BigQuery DataFrames API, adds new features, and introduces breaking changes.
You can use partial ordering mode in BigQuery DataFrames to generate efficient queries. This feature is generally available (GA).
April 09, 2025
Updated pricing, packaging, and setup guidance is now available for Gemini in BigQuery.
You can now combine raster and vector data with the ST_REGIONSTATS geography function to perform geospatial analysis in BigQuery. For more information, see Work with raster data and try the tutorial that shows you how to use raster data to analyze global temperature by country. This feature is in preview.
You can now use the Apache Arrow format to stream data to BigQuery with the Storage Write API. This feature is available in preview.
Analytics Hub has been renamed BigQuery sharing. You'll see this new name in the documentation set and the marketing collateral. The product functionality and endpoints remain the same. For more information, see Introduction to data governance in BigQuery.
Dataplex Catalog has been renamed BigQuery universal catalog. You'll see this new name in the product page of the Google Cloud console, the documentation set, and the marketing collateral. Universal catalog brings together the data catalog capabilities of Dataplex Catalog and the runtime metastore capabilities of BigQuery metastore. For more information, see Introduction to data governance in BigQuery.
April 08, 2025
BigQuery ML now offers a built-in TimesFM univariate time series forecasting model that implements Google Research's open source TimesFM model. You can use BigQuery ML's built-in TimesFM model with the AI.FORECAST function to perform forecasting without having to create and train your own model. This lets you avoid the need for model management.
To try using a TimesFM model with the AI.FORECAST function, see Forecast a time series with a TimesFM univariate model.
This feature is in preview.
You can now create, view, modify, and delete Apache Iceberg resources in BigQuery metastore. This feature is generally available (GA).
You can now connect BigQuery metastore to Apache Flink. This feature is generally available (GA).
April 07, 2025
BigQuery data preparation is generally available (GA). It offers AI-powered suggestions from Gemini for data cleansing, transformation, and enrichment. BigQuery supports visual data preparation pipelines and pipeline scheduling with Dataform.
You can now create remote models in BigQuery ML based on Llama and Mistral AI models in Vertex AI.
Use the ML.GENERATE_TEXT function with these remote models to perform generative natural language tasks for text stored in BigQuery tables. Try this feature with the Generate text by using the ML.GENERATE_TEXT function tutorial.
This feature is generally available (GA).
An updated version of JDBC driver for BigQuery is now available.
Smart-tuning is now supported for materialized views when they are in the same project as one of their base tables, or when they are in the project running the query. This feature is generally available (GA).
BigQuery ML now uses dynamic token-based batching for embedding generation requests. Dynamic token-based batching puts as many rows as possible into one request. This change boosts per-request utilization and improves scalability for any queries per minute (QPM) quota. Actual performance varies based on the embedding content length, with an average 10x improvement.
April 04, 2025
BigQuery ML now supports the following generative AI functions, which let you analyze text using a Vertex AI Gemini model. The function output includes a response that matches the type in the function name:
This feature is in preview.
April 03, 2025
BigQuery migration assessment now includes support for Amazon Redshift Serverless. This feature is in preview.
You can now generate structured data by using BigQuery ML's AI.GENERATE_TABLE function with Gemini 1.5 Pro, Gemini 1.5 Flash, and Gemini 2.0 Flash models. You can use the AI.GENERATE_TABLE function's output_schema argument to more easily format the model's response. The output_schema argument lets you specify a SQL schema for formatting, similar to the schema used in the CREATE TABLE statement. By creating structured output, you can more easily convert the function output into a BigQuery table.
Try this feature with the Generate structured data by using the AI.GENERATE_TABLE function tutorial.
This feature is in preview.
April 02, 2025
You can now create and use Python user-defined functions (UDFs) in BigQuery. Python UDFs support the use of additional libraries and external APIs. This feature is in preview.
The Python code that you generate using Gemini in BigQuery Notebooks is now much more likely to leverage your data. With this change, BigQuery Notebooks can intelligently pull relevant table names directly from your BigQuery project, resulting in personalized, executable Python code.
You can now generate Dataframes code in BigQuery Notebooks that use BigFrames libraries. In your code generation prompt, include the word BigFrames to generate code that uses BigQuery DataFrames. This feature is in preview.
April 01, 2025
Pipe syntax supports a linear query structure designed to make your queries easier to read, write, and maintain. This feature is generally available (GA).
You can use a CREATE MODEL statement to create a contribution analysis model in BigQuery ML. The top_k_insights_by_apriori_support and pruning_method model options are now supported. You can use a contribution analysis model with the ML.GET_INSIGHTS function to generate insights about changes to key metrics in your multi-dimensional data. The following metric types are supported:
This feature is generally available (GA).
March 31, 2025
Iceberg external tables now support merge-on-read. You can query Iceberg tables with position deletes and equality deletes. This feature is generally available (GA).
On the Scheduling page, you can now view existing schedules, create new schedules, and perform other actions for data preparations, notebooks, BigQuery pipelines, and scheduled queries. For more information, see Create a pipeline schedule. This feature is generally available (GA).
You can build BigQuery pipelines (formerly workflows), composed of SQL queries or notebooks, in BigQuery Studio. You can then run these pipelines on a schedule. You can also configure notebook runtimes for a pipeline, share a pipeline, or share a pipeline link. This feature is generally available (GA).
You can now define a _CHANGE_SEQUENCE_NUMBER for BigQuery change data capture (CDC) to manage streaming UPSERT ordering for BigQuery. This feature is generally available (GA).
BigQuery now supports subqueries in row level access policies. It also includes support for BigLake managed tables and the BigQuery Storage Read API. This feature is now generally available (GA).
You can now use BigQuery Data Transfer Service for Search Ads to view Performance Max (PMax) campaign data for the following tables:
- CartDataSalesStats
- ProductAdvertised
- ProductAdvertisedDeviceStats
- ProductAdvertisedConversionActionAndDeviceStats
This feature is generally available (GA).
You can now configure the repeat frequency of BigQuery Data Transfer Service for Google Ad Manager. This option has a default of every 8 hours and a minimum of every 4 hours. This feature is generally available (GA).
You can now skip loading match tables for BigQuery Data Transfer Service for Google Ad Manager. If match tables are not needed, you can set parameter load_match_tables to FALSE. This feature is generally available (GA).
Python
3.31.0 (2025-03-20)
Features
- Add query text and total bytes processed to RowIterator (#2140) (2d5f932)
- Add support for Python 3.13 (0842aa1)
Bug Fixes
- Adding property setter for table constraints, #1990 (#2092) (f8572dd)
- Allow protobuf 6.x (0842aa1)
- Avoid "Unable to determine type" warning with JSON columns in
to_dataframe(#1876) (968020d) - Remove setup.cfg configuration for creating universal wheels (#2146) (d7f7685)
Dependencies
You can include data preparation tasks in BigQuery pipelines that execute your code assets in sequence at a scheduled time. This feature is in Preview.
March 27, 2025
You can now enable metadata caching for SQL translation, which can significantly reduce latency for subsequent translation requests. This feature is in preview.
March 26, 2025
You can now set the column granularity when you create a search index, which stores additional column information in your search index to further optimize your search query performance. This feature is in preview.
March 25, 2025
BigQuery ML now supports visualization of model monitoring metrics. This feature lets you use charts and graphs to analyze model monitoring function output. The following functions support metric visualization:
ML.VALIDATE_DATA_SKEW: compute the statistics for a set of serving data, and then compare them to the statistics for the data used to train a BigQuery ML model in order to identify anomalous differences between the two data sets.ML.VALIDATE_DATA_DRIFT: compute and compare the statistics for two sets of serving data in order to identify anomalous differences between the two data sets.
This feature is in preview.
March 24, 2025
You can now use KLL quantile functions to efficiently compute approximate quantiles. This feature is in preview.
The BigQuery Data Transfer Service can now transfer reporting and configuration data from Google Analytics 4 into BigQuery. This feature is in preview.
We have redesigned the Add Data dialog to guide you through loading data into BigQuery with a source-first experience and enhanced search and filtering capabilities. This feature is generally available (GA).
Java
2.49.0 (2025-03-20)
Features
- bigquery: Implement getArray in BigQueryResultImpl (#3693) (e2a3f2c)
- Next release from main branch is 2.49.0 (#3706) (b46a6cc)
Bug Fixes
Dependencies
- Exclude io.netty:netty-common from org.apache.arrow:arrow-memor… (#3715) (11b5809)
- Update actions/upload-artifact action to v4.6.2 (#3724) (426a59b)
- Update actions/upload-artifact action to v4.6.2 (#3724) (483f930)
- Update dependency com.google.api.grpc:proto-google-cloud-bigqueryconnection-v1 to v2.61.0 (#3703) (53b07b0)
- Update dependency com.google.api.grpc:proto-google-cloud-bigqueryconnection-v1 to v2.62.0 (#3726) (38e004b)
- Update dependency com.google.apis:google-api-services-bigquery to v2-rev20250302-2.0.0 (#3720) (c0b3902)
- Update dependency com.google.apis:google-api-services-bigquery to v2-rev20250313-2.0.0 (#3723) (b8875a8)
- Update dependency com.google.cloud:google-cloud-datacatalog-bom to v1.65.0 (#3704) (53b68b1)
- Update dependency com.google.cloud:google-cloud-datacatalog-bom to v1.66.0 (#3727) (7339f94)
- Update dependency com.google.cloud:sdk-platform-java-config to v3.45.1 (#3714) (e4512aa)
- Update dependency com.google.oauth-client:google-oauth-client-java6 to v1.39.0 (#3710) (c0c6352)
- Update dependency com.google.oauth-client:google-oauth-client-jetty to v1.39.0 (#3711) (43b86e9)
- Update dependency node to v22 (#3713) (251def5)
- Update netty.version to v4.1.119.final (#3717) (08a290a)
Documentation
Go
1.67.0 (2025-03-14)
Features
- bigquery/reservation: Add a new field
enable_gemini_in_bigqueryto.google.cloud.bigquery.reservation.v1.Assignmentthat indicates if "Gemini in Bigquery"(https (601e742) - bigquery/reservation: Add a new field
replication_statusto.google.cloud.bigquery.reservation.v1.Reservationto provide visibility into errors that could arise during Disaster Recovery(DR) replication (#11666) (601e742) - bigquery/reservation: Add the CONTINUOUS Job type to
.google.cloud.bigquery.reservation.v1.Assignment.JobTypefor continuous SQL jobs (601e742) - bigquery: Support MetadataCacheMode for ExternalDataConfig (#11803) (af5174d), refs #11802
Bug Fixes
- bigquery: Increase timeout for storage api test and remove usage of deprecated pkg (#11810) (f47e038), refs #11801
- bigquery: Update golang.org/x/net to 0.37.0 (1144978)
Documentation
- bigquery/reservation: Remove the section about
EDITION_UNSPECIFIEDin the comment forslot_capacityin.google.cloud.bigquery.reservation.v1.Reservationto clarify that (601e742) - bigquery/reservation: Update the
google.api.field_behaviorfor the.google.cloud.bigquery.reservation.v1.Reservation.primary_locationand.google.cloud.bigquery.reservation.v1.Reservation.original_primary_locationfields to clarify that they areOUTPUT_ONLY(601e742)
March 20, 2025
BigQuery workflows have been renamed to BigQuery pipelines in the Google Cloud console. For more information, see Introduction to BigQuery pipelines.
You can now use repositories and workspaces in BigQuery to perform version control.
Repositories perform version control on files by using Git to record changes and manage file versions. You can use workspaces within repositories to edit the code stored in the repository.
You can have a repository use Git directly on BigQuery, or you can connect a repository to a third-party Git provider.
This feature is in preview.
You can now create remote models in BigQuery ML based on the Anthropic Claude model in Vertex AI.
Use the ML.GENERATE_TEXT function with these remote models to perform generative natural language tasks for text stored in BigQuery tables. Try this feature with the Generate text by using the ML.GENERATE_TEXT function tutorial.
You can also evaluate Claude models by using the ML.EVALUATE function.
This feature is generally available (GA).
March 17, 2025
You can now use EXPORT DATA statements to reverse ETL BigQuery data to Spanner. This feature is generally available (GA).
You can now create an external dataset in BigQuery that links to an existing database in Spanner. This feature is generally available (GA).
You can now use the TYPEOF function to determine the data type of an expression. This feature is generally available (GA).
March 13, 2025
Dataform now supports the CMEK organization policy.
You can now use Gemini Cloud Assist chat to generate SQL queries and Python code. This feature is in preview.
March 12, 2025
You can configure reusable, default Cloud resource connections in a project. Default connections are available in Preview.
An updated version of ODBC driver for BigQuery is now available.
March 10, 2025
Analytics Hub egress controls and data clean room subscriptions are now available in all BigQuery editions and on-demand pricing.
March 06, 2025
BigQuery Data Transfer Service now supports custom reports for Google Ads. You can use Google Ads Query Language (GAQL) queries in your transfer configuration to ingest custom Google Ads reports and fields beyond those available in the standard reports and fields. This feature is now generally available (GA).
March 04, 2025
BigQuery is now available in the Stockholm (europe-north2) region.
March 03, 2025
You can create a SQL user-defined aggregate function by using the CREATE AGGREGATE FUNCTION statement. This feature is generally available (GA).
Gemini in BigQuery can help you complete Python code with contextually appropriate recommendations that are based on content in the query editor. This feature is now generally available (GA).
Java
2.48.1 (2025-02-26)
Dependencies
- Update actions/upload-artifact action to v4.6.1 (#3691) (9c0edea)
- Update dependency com.google.api.grpc:proto-google-cloud-bigqueryconnection-v1 to v2.60.0 (#3680) (6d9a40d)
- Update dependency com.google.apis:google-api-services-bigquery to v2-rev20250216-2.0.0 (#3688) (e3beb6f)
- Update dependency com.google.cloud:google-cloud-datacatalog-bom to v1.64.0 (#3681) (9e4e261)
- Update dependency com.google.cloud:sdk-platform-java-config to v3.44.0 (#3694) (f69fbd3)
- Update dependency com.google.oauth-client:google-oauth-client-java6 to v1.38.0 (#3685) (53bd7af)
- Update dependency com.google.oauth-client:google-oauth-client-jetty to v1.38.0 (#3686) (d71b2a3)
- Update ossf/scorecard-action action to v2.4.1 (#3690) (cdb61fe)
Python
3.30.0 (2025-02-26)
Features
- Add roundingmode enum, wiring, and tests (#2121) (3a48948)
- Adds foreign_type_info attribute to table class and adds unit tests. (#2126) (2c19681)
- Support resource_tags for table (#2093) (d4070ca)
Bug Fixes
- Avoid blocking in download thread when using BQ Storage API (#2034) (54c8d07)
- Retry 404 errors in
Client.query(...)(#2135) (c6d5f8a)
Dependencies
- Updates required checks list in github (#2136) (fea49ff)
- Use pandas-gbq to determine schema in
load_table_from_dataframe(#2095) (7603bd7)
Documentation
February 25, 2025
You can now see a list of BigQuery API and service dependencies. You can also review the effects of disabling an API or service.
You can use the best sellers and price competitiveness migration guides to transition to the newer version of the reports. This feature is in preview.
BigQuery resource utilization charts provide metrics views and more chart configuration options in Preview.
February 24, 2025
You can now use the @@location system variable to set the location in which to run a query. This feature is in preview.
February 17, 2025
Subscriber email logging lets you log the principal identifiers of users who execute jobs and queries against linked datasets. You can enable logging at the listing level and the data exchange level (for all the listings in the data exchange). Once you enable and save subscriber email logging, this setting cannot be edited. This feature is in preview.
Java
2.48.0 (2025-02-13)
Features
Dependencies
- Update dependency com.google.api.grpc:proto-google-cloud-bigqueryconnection-v1 to v2.59.0 (#3660) (3a6228b)
- Update dependency com.google.apis:google-api-services-bigquery to v2-rev20250128-2.0.0 (#3667) (0b92af6)
- Update dependency com.google.cloud:google-cloud-datacatalog-bom to v1.63.0 (#3661) (9bc8c01)
- Update dependency com.google.cloud:sdk-platform-java-config to v3.43.0 (#3669) (4d9e0ff)
Documentation
February 10, 2025
BigQuery data preparation provides context-aware join operation recommendations from Gemini. Data preparation is available in Preview.
February 06, 2025
You can create a JavaScript user-defined aggregate function by using the CREATE AGGREGATE FUNCTION statement. This feature is generally available (GA).
February 03, 2025
The BigQuery ML ML.BUCKETIZE and ML.QUANTILE_BUCKETIZE functions now support formatting of the function output. You can use the output_format argument to format the function output as one of the following:
- A string in the format
bin_<bucket_index> - A string in interval notation
- A JSON-formatted string
You can now use the BY NAME and CORRESPONDING modifiers with set operations to match columns by name instead of by position. This feature is generally available (GA).
January 28, 2025
You can now view stored column usage information for a query job that performs vector search using stored columns. This feature is generally available (GA).
January 27, 2025
The following BigQuery ML generative AI features are now available:
- Creating a remote model based on an open model from Vertex Model Garden or Hugging Face that is deployed to Vertex AI. Options include Llama, Gemma, and other leading open text generation models.
- Using the
ML.GENERATE_TEXTfunction with this remote model to perform a broad range of generative AI tasks. - Using the
ML.EVALUATEfunction to evaluate the remote model.
Try these features with the
Generate text by using the ML.GENERATE_TEXT function
how-to topic and the
Generate text by using a Gemma open model and the ML.GENERATE_TEXT function
tutorial.
These features are generally available (GA).
We previously communicated that after January 27, 2025, a purchase would be required to use Gemini in BigQuery features. We are temporarily delaying enforcement of these procurement methods, and no purchase is required at this time. For more information, see Gemini for Google Cloud pricing.
You can now set conditional IAM access on BigQuery datasets with access control lists (ACLs). This feature is generally available (GA).
January 22, 2025
BigQuery metastore lets you access and manage metadata from a variety of processing engines, including BigQuery and Apache Spark. BigQuery metastore supports BigQuery tables and open formats such as Apache Iceberg. This feature is in preview.
January 21, 2025
In BigQuery ML, you can now evaluate Anthropic Claude models by using the
ML.EVALUATE function.
The quotas
for use of Anthropic Claude models in BigQuery ML have also been brought into
parity with Vertex AI quotas.
This feature is in preview.
You can use natural language to prepare data with Gemini in BigQuery.
Data preparation in BigQuery lets you test data preparations you're developing before you deploy and schedule runs in production. For more information, see Develop a data preparation.
January 20, 2025
Java
2.46.0 (2025-01-11)
Features
Bug Fixes
- NPE when reading BigQueryResultSet from empty tables (#3627) (9a0b05a)
- test: Force usage of ReadAPI (#3625) (5ca7d4a)
Dependencies
- Update actions/upload-artifact action to v4.5.0 (#3620) (cc25099)
- Update actions/upload-artifact action to v4.6.0 (#3633) (ca20aa4)
- Update dependency com.google.api.grpc:proto-google-cloud-bigqueryconnection-v1 to v2.57.0 (#3617) (51370a9)
- Update dependency com.google.api.grpc:proto-google-cloud-bigqueryconnection-v1 to v2.58.0 (#3631) (b0ea0d5)
- Update dependency com.google.apis:google-api-services-bigquery to v2-rev20241222-2.0.0 (#3623) (4061922)
- Update dependency com.google.cloud:google-cloud-datacatalog-bom to v1.61.0 (#3618) (6cba626)
- Update dependency com.google.cloud:google-cloud-datacatalog-bom to v1.62.0 (#3632) (e9ff265)
- Update dependency com.google.cloud:sdk-platform-java-config to v3.41.1 (#3628) (442d217)
- Update dependency com.google.oauth-client:google-oauth-client-java6 to v1.37.0 (#3614) (f5faa69)
- Update dependency com.google.oauth-client:google-oauth-client-jetty to v1.37.0 (#3615) (a6c7944)
- Update github/codeql-action action to v2.27.9 (#3608) (567ce01)
- Update github/codeql-action action to v2.28.0 (#3621) (e0e09ec)
Python
3.28.0 (2025-01-15) - YANKED
Reason this release was yanked:
This turned out to be incompatible with pandas-gbq. For more details, see issue.
Features
- Add property for
allowNonIncrementalDefinitionfor materialized view (#2084) (3359ef3) - Add property for maxStaleness in table definitions (#2087) (729322c)
- Add type hints to Client (#2044) (40529de)
- Adds ExternalCatalogDatasetOptions and tests (#2111) (b929a90)
- Adds ForeignTypeInfo class and tests (#2110) (55ca63c)
- Adds new input validation function similar to isinstance. (#2107) (a2bebb9)
- Adds StorageDescriptor and tests (#2109) (6be0272)
- Adds the SerDeInfo class and tests (#2108) (62960f2)
- Migrate to pyproject.toml (#2041) (1061611)
- Preserve unknown fields from the REST API representation in
SchemaField(#2097) (aaf1eb8) - Resource tags in dataset (#2090) (3e13016)
- Support setting max_stream_count when fetching query result (#2051) (d461297)
Bug Fixes
Documentation
January 17, 2025
The BigQuery Data Transfer Service can now transfer data from the following data sources:
Transfers from these data sources are supported in Preview.
In the navigation menu, you can now go to the Settings page to set default settings that are applied when you start a session in BigQuery Studio. This feature is in preview.
January 16, 2025
The BigQuery migration assessment for Oracle now includes a total cost of ownership (TCO) calculator that provides an estimation of compute and storage costs for migrating your Oracle data warehouse to BigQuery. This feature is in preview.
We have rearranged the navigation menu into new categories. This feature is generally available (GA).
January 13, 2025
In BigQuery ML, you can now forecast multiple time series at once by using the
new
TIME_SERIES_ID_COL option
that is available in ARIMA_PLUS_XREG multivariate time series models. Try this
feature with the
Forecast multiple time series with a multivariate model
tutorial.
This feature is in preview.
You can now use BigQuery Omni Virtual Private Cloud (VPC) allowlists to restrict access to AWS S3 buckets and Azure Blob Storage from specific BigQuery Omni VPCs. This feature is generally available (GA).
January 02, 2025
An updated version of JDBC driver for BigQuery is now available.
November 14, 2024
You can try Gemini in BigQuery at no charge until January 27, 2025. After that date, to continue to use Gemini in BigQuery you must do one of the following:
- Purchase and assign BigQuery Enterprise Plus edition reservations to projects that use Gemini in BigQuery.
- Purchase Gemini Code Assist Enterprise.
October 10, 2024
You can now export and load Parquet files that include GeoParquet metadata. This feature is generally available (GA).
August 26, 2024
You can now create remote models in BigQuery ML based on the Anthropic Claude model in Vertex AI.
Use the
ML.GENERATE_TEXT function with these remote models to perform generative natural language tasks for text
stored in BigQuery tables. Try this feature with the
Generate text by using the ML.GENERATE_TEXT function
how-to topic.
This feature is in preview.
July 30, 2024
You can now use the output_dimensionality argument of the
ML.GENERATE_EMBEDDING function
when you use the function with a
remote model
based on a
Vertex AI multimodalembedding model. The output_dimensionality argument lets you specify the number of dimensions
to use when generating embeddings. This feature is in Preview.
July 23, 2024
You can now configure SAP Datasphere connections with network attachments to help secure connections. SAP Datasphere connections are in preview.
July 01, 2024
Data publishers can now share Pub/Sub topics and manage subscriptions in Analytics Hub. This feature is in preview.
June 25, 2024
You can now use the BigQuery JupyterLab plugin to explore your data, use BigQuery DataFrames in a Jupyter notebook, and deploy a BigQuery DataFrames notebook to Cloud Composer. This feature is in preview.
June 13, 2024
You can now schedule notebooks. This feature is available in preview.
May 06, 2024
BigQuery Managed Disaster Recovery provides managed failover and redundant compute capacity for business critical workloads. It is intended for use in the case of a total region outage and is supported with the BigQuery Enterprise Plus edition only. This feature is now available in preview.
April 04, 2024
The allow_non_incremental_definition option and max_staleness option for materialized views are now generally available (GA). The allow_non_incremental_definition option supports an expanded range of SQL queries to create materialized views, and the max_staleness option provides consistently high performance with controlled costs when processing large, frequently changing datasets.
April 03, 2024
Collation now supports the following generally available (GA) features:
- The underscore in the
LIKEoperator. - Comparison support for the
STRUCTdata type with the following operators and conditional expressions:=,!=,INandCASE.
March 20, 2024
You can now view lists of all saved queries and all notebooks in your project. These features are available in preview.
December 12, 2023
The following BigQuery cross-cloud features are now in preview:
- You can now take advantage of the benefits of materialized views over Amazon S3 metadata cache-enabled BigLake tables.
- You can create materialized view replicas of materialized views over Amazon S3 metadata cache-enabled BigLake tables. Materialized view replicas let you use the materialized view data in queries while avoiding data egress costs and improving query performance.
November 14, 2023
You can now see query performance insights about partition skew. This feature is in preview.
October 09, 2023
Queries now support additional ways to work with grouping sets, which include:
GROUP BY GROUPING SETSclause (new): Produce aggregated data for one or more grouping sets.GROUP BY CUBEclause (new): Produce aggregated data for all grouping set permutations.GROUP BY ROLLUPclause (update): You can now include groupable items sets in this clause.GROUPINGfunction (new): Check if a groupable value in theGROUP BYclause is aggregated.
This feature is in preview.
September 25, 2023
Authorized stored procedures are now generally available (GA). This feature lets you share stored procedures with users or groups without giving them direct access to the underlying tables.
August 29, 2023
Duet AI in BigQuery, an AI-powered collaborator in Google Cloud, can help you complete, generate, and explain SQL queries. This feature is in preview.
August 07, 2023
The following JSON functions are now generally available (GA).
JSON_ARRAY: Creates a JSON array.JSON_ARRAY_APPEND: Appends JSON data to the end of a JSON array.JSON_ARRAY_INSERT: Inserts JSON data into a JSON array.JSON_OBJECT: Creates a JSON object.JSON_REMOVE: Produces JSON with the specified JSON data removed.JSON_SET: Inserts or replaces JSON data.JSON_STRIP_NULLS: Removes JSON nulls.LAX_BOOL: Attempts to convert a JSON value to a SQLBOOLvalue.LAX_FLOAT64: Attempts to convert a JSON value to a SQLFLOAT64value.LAX_INT64: Attempts to convert a JSON value to a SQLINT64value.LAX_STRING: Attempts to convert a JSON value to a SQLSTRINGvalue.
August 03, 2023
Cloud console updates: The following features are now available in preview:
- On the Welcome page, in the Recently accessed section, you can view your 10 most recently accessed resources.
- After you run a query in the query editor, in the Chart tab, you can see the visualization of your query results.
July 05, 2023
The slot estimator now provides cost-optimal commitment and autoscale recommendations based on editions pricing and historical performance metrics. This feature is in preview.
BigQuery capacity commitments have changed as follows:
- Annual commitments are now only available in Enterprise or Enterprise Plus edition. Flat-rate annual commitments are no longer available. For more information about pricing, see Capacity compute (analysis) pricing.
- Monthly and flex commitments are no longer available. For more information about commitment options, see Capacity commitment plans.
May 25, 2023
The BigQuery partitioning and clustering recommender is now in preview. The recommender analyzes your BigQuery tables to identify partitioning or clustering opportunities for potential cost savings. You can view partition or cluster recommendations through the BigQuery UI or recommender API. You can also apply recommendations directly to your BigQuery tables.
May 09, 2023
You can now view BI Engine Top Tables Cached Bytes, BI Engine Query Fallback Count, and Query Execution Count as dashboard metrics for BigQuery. This feature is now generally available (GA).
April 04, 2023
BigQuery is now available in the Israel (me-west1) region.
February 27, 2023
The multivariate time-series forecasting model ARIMA_PLUS_XREG is now available to on-demand users.
December 15, 2022
You can now access and query Cloud SQL data over a private connection. This feature is generally available (GA).
October 11, 2022
You can now use stored procedures for Apache Spark. This feature is in preview.
September 15, 2022
BigQuery ML is now available in the Madrid (europe-southwest1), Milan (europe-west8), and [Paris (europe-southwest1)]https://cloud.google.com/bigquery/docs/locations#regional-locations) regions. The Madrid and Paris regions have the lowest carbon impact.
August 10, 2022
You can now set default configurations at a project or organization level. This feature is now generally available (GA).
You can now manage query execution priority for Cloud Spanner federated queries. This feature is now generally available (GA).
July 11, 2022
The google.cloud.bigquery.reservation.v1beta1.api package is deprecated and will be removed on September 27, 2022. After that date, requests to that package will fail. Data created by using google.cloud.bigquery.reservation.v1beta1.api are accessible by using the google.cloud.bigquery.reservation.v1.api package.
Next steps:
- If you use the API directly, you should switch to google.cloud.bigquery.reservation.v1.api, the GA version of the API, to prevent any impact on your workflow.
- If you only use the Cloud console to manage BigQuery reservations, no action is needed.
- If you use the bq command-line tool to manage BigQuery reservations, upgrade the tool to the latest version.
June 29, 2022
You can now set the view field in the tables.get() API method to indicate which table information is returned. Setting the value to BASIC reduces latency by omitting some storage statistics.
April 25, 2022
Use the
TABLE_STORAGE view to get a snapshot of current storage usage for tables and materialized views. This feature is now in
Preview.
December 06, 2021
Anomaly detection in BigQuery ML is now generally available (GA). You can use the ML.DETECT_ANOMALIES function with the ARIMA_PLUS model to detect anomalies in time-series data. You can also use this function with the K-means, Autoencoder, or PCA models to detect anomalies in independent and identically distributed (IID) data.
July 26, 2021
Time series models now support holiday effects for weekly time series, in addition to the daily time series that was previously supported. This feature is now generally available (GA).
June 29, 2021
BigQuery ML is now available in the Delhi (asia-south2) region.
June 28, 2021
Audit logging, Cloud Logging, and Cloud Monitoring for the BigQuery Data Transfer Service are now generally available (GA).
June 21, 2021
BigQuery is now available in the Melbourne (australia-southeast2) region.
April 12, 2021
The BigQuery Admin Resource Charts Preview is now available for Reservation users, enabling administrators to more easily monitor and troubleshoot their BigQuery environment. It provides visibility into key metrics such as slot consumption, job concurrency, and job execution time across the entire organization.
February 02, 2021
Updated version of Magnitude Simba JDBC driver includes bug and security fixes and enhancements for additional DDL keywords and dynamic SQL.
January 29, 2021
Clustered tables now support the DATETIME type for clustering columns. For more information, see Creating and using clustered tables. This feature is generally available.
October 14, 2020
BigQuery now supports the following new statements. These statements are generally available (GA).
Queries can now have duplicate column names.
August 26, 2020
INFORMATION_SCHEMA views for BigQuery reservations are now Generally Available (GA).
August 18, 2020
You can now explicitly assign projects to use on-demand pricing with Reservations. See Assign a project to None.
June 08, 2020
BigQuery Data Transfer Service is now available in the Jakarta (asia-southeast2) region.
April 30, 2020
The BigQuery Data Transfer Service is now available in the Taiwan (asia-east1) region.
April 22, 2020
BigQuery ML now supports exporting BigQuery ML models to Cloud Storage and using them for online prediction. This feature is in beta. For more information, see Exporting models.
April 14, 2020
BigQuery Data Transfer Service now supports Google Merchant Center data transfers for best sellers data.
April 09, 2020
Scheduling queries no longer requires the bigquery.transfers.update permission. The bigquery.jobs.create permission can now be used to schedule queries. See Scheduling queries for details.
April 08, 2020
BigQuery materialized views are now available as a beta release. For more information, see Introduction to materialized views .
April 02, 2020
BigQuery Reservations is now available in all BigQuery regions.
February 20, 2020
Added support for custom queries and views from Data Studio.
November 22, 2019
You can now use INFORMATION_SCHEMA views to get routine metadata in BigQuery. INFORMATION_SCHEMA is currently in beta.
November 20, 2019
BigQuery is now available in the South Carolina (us-east1) region.
October 03, 2019
BigQuery Data Transfer Service now supports Search Ads 360 data transfers. Search Ad 360 transfers are in beta.
The ability to use scripting, stored procedures, and temporary tables is now in Beta.
August 07, 2019
You can now query data in BigQuery and Cloud SQL with a federated query. Cloud SQL federated queries are now in beta.
August 05, 2019
The BigQuery Storage API now supports reading data from BigQuery Storage in ARROW format. The BigQuery Storage API is currently in beta.
April 18, 2019
BigQuery is now available in the Osaka (asia-northeast2) region. For upcoming regional launches, see the Google Cloud blog.
February 15, 2019
BigQuery is now available in the São Paulo (southamerica-east1) region. For upcoming regional launches, see the Google Cloud blog.
December 05, 2018
You can now set or update a default partition expiration time on a dataset.
November 26, 2018
Updated version of the Simba ODBC drivers.
November 08, 2018
BigQuery ML pricing is now available.
October 03, 2018
Support for Cloud Storage Transfers is now in Beta.
March 05, 2018
BigQuery data definition language now supports creating a table from the result of a query.
January 05, 2018
ISOWEEK and ISOYEAR are now supported by the following functions: DATE_TRUNC, DATETIME_TRUNC, TIMESTAMP_TRUNC, DATE_DIFF, and DATETIME_DIFF.
August 17, 2017
Updated versions of Simba ODBC and JDBC releases.
May 23, 2017
Added troubleshooting documentation for the BigQuery Data Transfer Service:
May 12, 2017
Announced availability of new public datasets:
February 01, 2017
Announced support for copying non-partitioned tables to partitioned tables. For more information, see Copying to partitioned tables.
December 22, 2016
If you use OMIT...IF to exclude a portion of a record in a repeating field, and the query also selects other independently repeating fields, BigQuery now returns an error. To avoid this error, migrate your query to standard SQL.
November 30, 2016
Announced availability of JSON functions in standard SQL.
March 23, 2016
Announced Long Term Storage pricing.
August 25, 2015
Quota updates: * Increased the concurrent rate limit to 50 queries. * Increased the daily query limit to 100,000 queries.
March 25, 2014
Added views. A view is a virtual table defined by a SQL query.
September 18, 2013
Added support for streaming inserts.
Added new aggregate functions.
June 11, 2013
Added query caching.
August 17, 2012
API: Improved validation of project IDs
July 16, 2012
BigQuery Browser Tool: Add a drag handle to the separator below the query editor
May 30, 2012
API: Added token based pagination support for list operations. Clients can use token based pagination to page through a single table snapshot. Subsequent changes to the table are not reflected when paging through list results.
May 11, 2012
API: Better errors for field/rows being too long
February 01, 2012
BigQuery Browser Tool
Show previous query resultsoption in the query panel- The current project view is now highlighted
- "Refresh" option in the projects drop-down menu