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BigQuery

Cloud data warehouse to power your data-driven innovation

BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data. Use built-in ML/AI and BI for insights at scale. 

New customers get $300 in free credits to spend on BigQuery.

All customers get 10 GB storage and up to 1 TB queries free per month.

Features

Unified experience for all analytics users

BigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.

Duet AI in BigQuery

An AI collaborator integrated into BigQuery, Duet AI in BigQuery provides contextual code assistance for writing SQL and Python. It auto-suggests functions, code blocks, and fixes. With chat assistance, you can use natural language to get real-time guidance on performing specific tasks, reducing your need to search for documentation. Learn more about Duet AI in Google Cloud.

Flexibility, predictable pricing, and best price performance

BigQuery editions allow you to pick the right feature set for individual workload requirements with the ability to mix and match for the right price-performance. Compute capacity autoscaling adds fine-grained compute resources in real time to match the needs of your workload demands, and ensure you only pay for the compute capacity you use. With compressed storage pricing, you can reduce your storage costs while increasing your data footprint at the same time.

Built-in machine learning

BigQuery ML enables data scientists and data analysts to build and operationalize ML models on planet-scale structured, semi-structured, and now unstructured data directly inside BigQuery, using simple SQL—in a fraction of the time. Export BigQuery ML models for online prediction into Vertex AI or your own serving layer. Learn more about the models we currently support.

Analyze and share data across clouds

BigQuery Omni is a fully managed, multicloud analytics solution that allows for cost-effective and secure data analysis across clouds and shares results within a single pane of glass. Within BigQuery Analytics Hub, securely exchange data assets internally and across organizations and enhance analysis with commercial, public, and Google datasets. Create and manage data clean rooms for privacy-centric measurement, data sharing, and collaboration across organizations without moving or copying data.

Real-time analytics with streaming data pipelines

BigQuery has built-in capabilities that ingest streaming data and make it immediately available to query, along with native integrations to streaming products, like Dataflow. Analyze large datasets interactively with BigQuery BI Engine, an in-memory analysis service that offers sub-second query response time and high concurrency. Accelerate query performance and reduce costs within your environment with BigQuery materialized views.

Unify, manage, and govern all types of data

Query all data types with BigQuery: structured, semi-structured, and unstructured. Use BigLake to explore and unify different data types and build advanced models. Centrally discover, manage, monitor, and govern data across data lakes, data warehouses, and data marts with consistent controls with Dataplex, an intelligent data fabric that enables organizations to provide access to trusted data. 

Share insights with built-in business intelligence

With built-in business intelligence, create and share insights in a few clicks with Looker Studio or build data-rich experiences that go beyond BI with Looker. Analyze billions of rows of live BigQuery data in Google Sheets with familiar tools, like pivot tables, charts, and formulas, to easily derive insights from big data with Connected Sheets

Data governance and security

BigQuery's integration with security and privacy services from Google Cloud provides strong security and fine-grained governance controls, down to the column level and row level. Rest assured knowing your data is encrypted at rest and in transit by default. 

Geospatial analysis with BigQuery

BigQuery geospatial uniquely combines the serverless architecture of BigQuery with native support for geospatial analysis, so you can augment your analytics workflows with location intelligence. 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 common geospatial data formats.

Real-time change data capture and replication

Synchronize data across heterogeneous databases, storage systems, and applications reliably and with minimal latency with Datastream. Datastream integrates with purpose-built and extensible Dataflow templates to pull change streams written to Cloud Storage, and create up-to-date replicated tables in BigQuery for real-time analytics.

How It Works

BigQuery's serverless architecture lets you use SQL queries to analyze your data. You can store and analyze your data within BigQuery or use BigQuery to assess your data where it lives. To test how it works for yourself, query data—without a credit card—using the BigQuery sandbox.

BigQuery product UI
Demo: Solving business challenges with an end-to-end analysis in BigQuery

Common Uses

Transfer data into BigQuery

Bring any data into BigQuery

Make analytics easier by bringing together data from multiple sources into BigQuery. You can upload data files from local sources, Google Drive, or Cloud Storage buckets, use BigQuery Data Transfer Service (DTS), Cloud Data Fusion plugins, replicate data from relational databases with Datastream for BigQuery, or leverage Google's industry-leading data integration partnerships.
Learn about third-party transfers
ways to bring data into BigQuery

Bring any data into BigQuery

Make analytics easier by bringing together data from multiple sources into BigQuery. You can upload data files from local sources, Google Drive, or Cloud Storage buckets, use BigQuery Data Transfer Service (DTS), Cloud Data Fusion plugins, replicate data from relational databases with Datastream for BigQuery, or leverage Google's industry-leading data integration partnerships.
Learn about third-party transfers
ways to bring data into BigQuery

Data warehouse migration

Migrate data warehouses to BigQuery

Solve for today’s analytics demands and seamlessly scale your business by moving to Google Cloud’s enterprise data warehouse. Streamline your migration path from Netezza, Oracle, Redshift, Teradata, or Snowflake to BigQuery using the free and fully managed BigQuery Migration Service.
Learn about BigQuery Migration Service for a comprehensive data warehouse migration
Diagram

Migrate data warehouses to BigQuery

Solve for today’s analytics demands and seamlessly scale your business by moving to Google Cloud’s enterprise data warehouse. Streamline your migration path from Netezza, Oracle, Redshift, Teradata, or Snowflake to BigQuery using the free and fully managed BigQuery Migration Service.
Learn about BigQuery Migration Service for a comprehensive data warehouse migration
Diagram

Real-time analytics

Event-driven analysis

Gain a competitive advantage by responding to business events in real time with event-driven analysis. Built-in streaming capabilities automatically ingest streaming data and make it immediately available to query. This allows you to stay agile and make business decisions based on the freshest data. Or use Dataflow to enable fast, simplified streaming data pipelines for a comprehensive solution.
Learn more about streaming data into BigQuery
streaming analytics architecture

    Event-driven analysis

    Gain a competitive advantage by responding to business events in real time with event-driven analysis. Built-in streaming capabilities automatically ingest streaming data and make it immediately available to query. This allows you to stay agile and make business decisions based on the freshest data. Or use Dataflow to enable fast, simplified streaming data pipelines for a comprehensive solution.
    Learn more about streaming data into BigQuery
    streaming analytics architecture

      Predictive analytics

      Predict business outcomes with leading AI/ML

      Predictive analytics can be used to streamline operations, boost revenue, and mitigate risk. BigQuery ML democratizes the use of ML by empowering data analysts to build and run models using existing business intelligence tools and spreadsheets. Predictive analytics can guide business decision-making across the organization.
      View smart analytics design patterns for predictive analytics use cases
      ML diagram

      Predict business outcomes with leading AI/ML

      Predictive analytics can be used to streamline operations, boost revenue, and mitigate risk. BigQuery ML democratizes the use of ML by empowering data analysts to build and run models using existing business intelligence tools and spreadsheets. Predictive analytics can guide business decision-making across the organization.
      View smart analytics design patterns for predictive analytics use cases
      ML diagram

      Log analytics

      Analyze log data

      Analyze and gain deeper insights into your logging data with BigQuery. You can store, explore, and run queries on generated data from servers, sensors, and other devices simply using GoogleSQL. Additionally, you can analyze log data alongside the rest of your business data for broader analysis all natively within BigQuery.
      Learn how to analyze BigQuery usage

      Analyze log data

      Analyze and gain deeper insights into your logging data with BigQuery. You can store, explore, and run queries on generated data from servers, sensors, and other devices simply using GoogleSQL. Additionally, you can analyze log data alongside the rest of your business data for broader analysis all natively within BigQuery.
      Learn how to analyze BigQuery usage

      Marketing analytics

      Increase marketing ROI and performance with data and AI

      Bring the power of Google AI to your marketing data by unifying marketing and business data sources in BigQuery. Get a holistic view of the business, increase marketing ROI and performance using more first-party data, and deliver personalized and targeting marketing at scale with ML/AI built-in. Share insights and performance with Looker Studio or Connected Sheets.
      Explore data and AI solutions built for marketing use cases
      Marketing data warehouse diagram

        Increase marketing ROI and performance with data and AI

        Bring the power of Google AI to your marketing data by unifying marketing and business data sources in BigQuery. Get a holistic view of the business, increase marketing ROI and performance using more first-party data, and deliver personalized and targeting marketing at scale with ML/AI built-in. Share insights and performance with Looker Studio or Connected Sheets.
        Explore data and AI solutions built for marketing use cases
        Marketing data warehouse diagram

          Data clean rooms

          BigQuery data clean rooms for privacy-centric data sharing

          Create a low-trust environment for you and your partners to collaborate without copying or moving the underlying data right within BigQuery. This allows you to perform privacy-enhancing transformations in BigQuery SQL interfaces and monitor usage to detect privacy threats on shared data. Benefit from BigQuery scale without needing