A serverless, highly scalable, and cost-effective cloud data warehouse designed to help you make informed decisions quickly, so you can transform your business with ease

Accelerate time-to-value with a fully managed and serverless cloud data warehouse that is easy to set up and manage and doesn’t require a database administrator. Jump-start data analysis cost effectively and uncover meaningful insights to stay competitive.

  • Quickly analyze gigabytes to petabytes of data using ANSI SQL at blazing-fast speeds, and with zero operational overhead
  • Efficiently run analytics at scale with a 26%–34% lower three-year TCO than cloud data warehouse alternatives
  • Seamlessly democratize insights with a trusted and more secure platform that scales with your needs

Reveal insights with real-time and predictive analytics

Query streaming data in real time and get up-to-date information on all your business processes. Predict business outcomes easily with built-in machine learning and without the need to move data.

Access data and share insights with ease

Securely access and share analytical insights in your organization with a few clicks. Easily create stunning reports and dashboards using popular business intelligence tools, out of the box.

Protect your data and operate with trust

Have peace of mind with BigQuery’s robust security, governance, and reliability controls that offer high availability and a 99.9% uptime SLA. Data is encrypted by default and includes support for customer-managed encryption keys.

Key features

BigQuery ML

BigQuery ML enables data scientists and data analysts to build and operationalize ML models on planet-scale structured or semi-structured data, directly inside BigQuery, using simple SQL—in a fraction of the time. Learn more about the models we currently support.

BigQuery BI Engine

BigQuery BI Engine is a blazing-fast in-memory analysis service for BigQuery that allows users to analyze large and complex datasets interactively with sub-second query response time and high concurrency. BigQuery BI Engine seamlessly integrates with familiar tools like Google Data Studio, Looker, Sheets, and more to accelerate data exploration and analysis.

BigQuery GIS

BigQuery GIS uniquely combines the serverless architecture of BigQuery with native support for geospatial analysis, making BigQuery the only cloud data warehouse with built-in GIS functionality. Simplify your analyses, see spatial data in fresh ways, and unlock entirely new lines of business with support for arbitrary points, lines, polygons, and multi-polygons in WKT, WKB, and GeoJSON formats.

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Customer stories


  • More than 1 billion data points analyzed daily

  • ML model outcomes tell exactly how to maximize use of assets and scale for the holidays

  • Prescriptive analytics allows UPS to achieve true supply-chain visibility and efficiency


  • Retail and consumer goods

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What’s new


Quickstart using the web UI

Learn how to use the BigQuery web UI in the GCP Console as a visual interface to complete tasks like running queries, loading data, and exporting data.

Quickstart using the BigQuery command-line tool

Learn how to use the BigQuery command-line tool to run queries, load data, and export data.

Quickstart using client libraries

Learn how to use the BigQuery API in your favorite programming language using the Google Cloud client libraries.

Creating and using tables

Learn how to create and use standard tables in BigQuery.

Specifying a schema

Learn how to create and update a schema for your table.

Protecting data with Cloud KMS keys

Learn how you can use customer-managed encryption keys (CMEK) for BigQuery.

Controlling access to datasets

Learn how to control access to datasets in BigQuery.

Common use cases

Data warehouse modernization

Migrate your on-premises legacy data warehouse to an agile, cloud-based data warehouse solution. Focus on insights instead of buying and maintaining your own hardware and database servers. Jump-start your modernization journey with easy-to-use tools and a global partner support system. Learn more.

Migrating data from Teradata

The combination of the BigQuery Data Transfer Service and a special migration agent lets you copy data from an on-premises data warehouse environment such as Teradata, to BigQuery.

The on-premises migration agent communicates with the BigQuery Data Transfer Service to copy tables from your Teradata environment to BigQuery. And you can monitor recurring data loads to BigQuery by using the BigQuery Data Transfer Service's web UI.

A simplified, overall flow of data between an on-premises data warehouse like Teradata and BigQuery.
Migrating from Amazon Redshift to BigQuery

The BigQuery Data Transfer Service allows you to copy your data from an Amazon Redshift data warehouse to BigQuery. The service will engage migration agents in Google Kubernetes Engine and trigger an unload operation from Amazon Redshift to a staging area in an Amazon S3 bucket. Then the BigQuery Data Transfer Service transfers your data from the Amazon S3 bucket to BigQuery.

The overall flow of data between an Amazon Redshift data warehouse and BigQuery during a migration.

Marketing analytics

Bring all your marketing and customer data together to get a clearer picture of the customer journey, predict marketing and business outcomes, and create a more personalized experience for your customers. Learn more.

All features

Serverless With serverless data warehousing, Google does all resource provisioning behind the scenes, so you can focus on data and analysis rather than worrying about upgrading, securing, or managing the infrastructure.
Real-time analytics BigQuery’s high-speed streaming insertion API provides a powerful foundation for real-time analytics, making your latest business data immediately available for analysis. You can also leverage Pub/Sub and Dataflow to stream data into BigQuery.
Automatic high availability BigQuery transparently and automatically provides highly durable, replicated storage in multiple locations and high availability with no extra charge and no additional setup.
Standard SQL BigQuery supports a standard SQL dialect that is ANSI:2011 compliant, which reduces the need for code rewrites. BigQuery also provides ODBC and JDBC drivers at no cost to ensure your current applications can interact with its powerful engine.
Federated query and logical data warehousing Through powerful federated queries, BigQuery can process external data sources in object storage (Cloud Storage), i.e. Parquet and ORC open source file formats, transactional databases (Bigtable, Cloud SQL), or spreadsheets in Drive — all without duplicating data.
Convergence of data warehouse and data lake Run open source data science workloads (Spark, TensorFlow, Dataflow and Apache Beam, MapReduce, Pandas and scikit-learn) directly on BigQuery using the Storage API. The Storage API provides a much simpler architecture and less data movement, and doesn't need to have multiple copies of the same data.
Storage and compute separation With BigQuery’s separated storage and compute, you have the option to choose the storage and processing solutions that make sense for your business and control access and costs for each.
Automatic backup and easy restore BigQuery automatically replicates data and keeps a seven-day history of changes, allowing you to easily restore and compare data from different times.
Geospatial data types and functions BigQuery GIS brings SQL support for arbitrary points, lines, polygons, and multi-polygons in WKT and GeoJSON format. You can simplify your geospatial analyses, see your location-based data in new ways, or unlock entirely new lines of business.
Data transfer service The BigQuery Data Transfer Service automatically transfers data from external data sources, like Google Marketing Platform, Google Ads, YouTube, and partner SaaS applications to BigQuery on a scheduled and fully managed basis. Users can also easily transfer data from Teradata and Amazon S3 to BigQuery.
Big data ecosystem integration With Dataproc and Dataflow, BigQuery provides integration with the Apache big data ecosystem, allowing existing Hadoop/Spark and Beam workloads to read or write data directly from BigQuery using the Storage API.
Petabyte scale Get great performance on your data, while knowing you can scale seamlessly to store and analyze petabytes to exabytes of data with ease.
Flexible pricing models On-demand pricing lets you pay only for the storage and compute that you use. Flat-rate pricing with Reservations enables high-volume users or enterprises to choose price predictability and workload management seamlessly. For more information, see BigQuery pricing or cost controls.
Data governance and security BigQuery provides strong security and governance controls with fine-grained Identity and Access Management, and your data is always encrypted at rest and in transit.
Geo-expansion BigQuery gives you the option of geographic data control (in US, Asia, and European locations), without the headaches of setting up and managing clusters and other computing resources in-region.
Foundation for AI Besides bringing ML to your data with BigQuery ML, integrations with AI Platform Prediction and TensorFlow enable you to train powerful models on structured data in minutes with just SQL.
Foundation for BI BigQuery forms the data warehousing backbone for modern BI solutions and enables seamless data integration, transformation, analysis, visualization, and reporting with tools from Google and our technology partners.
Flexible data ingestion Automatically move data from hundreds of popular business SaaS applications into BigQuery for free with Data Transfer Service (DTS) or leverage data integration tools like Cloud Data Fusion, Informatica, Talend, and more. Load and transform data at any scale from hybrid and multi-cloud applications.
Programmatic interaction BigQuery provides a REST API for easy programmatic access and application integration. Client libraries are available in Java, Python, Node.js, C#, Go, Ruby, and PHP. Business users can use Google Apps Script to access BigQuery from Sheets.
Rich monitoring and logging BigQuery provides rich monitoring, logging, and alerting through Cloud Audit Logs and it can serve as a repository for logs from any application or service using Cloud Logging.
Public datasets Google Cloud Public Datasets offer a powerful data repository of more than 100 high-demand public datasets from different industries. Google provides free storage for all public datasets, and customers can query up to 1 TB of data per month at no cost.
Commercial datasets Commercial data providers host their data offerings directly in BigQuery and Cloud Storage, which means that once you license a dataset from one of our partners, you can access this data immediately and process it in place without having to store or move any data.


BigQuery charges for data storage, streaming inserts, and querying data, but loading and exporting data are free of charge. For detailed pricing information, please view the pricing guide.

$0.02 per GB, per month
$0.01 per GB, per month for long-term storage
Streaming Inserts $0.01 per 200 MB
Loading, copying, or exporting data; metadata operations Free

If you pay in a currency other than USD, the prices listed in your currency on Cloud Platform SKUs apply.

When querying data, you can choose from two different pricing options:

$5 per TB
First terabyte (1 TB) per month is free*
Flat-rate pricing
Starts at $10,000/month for a dedicated reservation of 500 slots.
$30 per month per slot for Flex Slots.
For more information, see flat-rate pricing.

See additional details for BigQuery ML pricing.

If you pay in a currency other than USD, the prices listed in your currency on Cloud Platform SKUs apply.

* The first 1 TB of data processed with BigQuery each month is free.

Note: BigQuery’s quota policy applies for these operations.

View pricing details


BigQuery unlocks the full potential of data warehousing in the cloud for a broad array of tools and partners. From data integration to analytics, Google Cloud partners have integrated their industry-leading tools with BigQuery for loading, transforming, and visualizing data.

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