Google is a leader, positioned furthest in vision, in the 2024 Gartner Magic Quadrant for Cloud DBMS. Learn more.

BigQuery

From data warehouse to a unified, AI-ready data platform

BigQuery is a fully managed, AI-ready data analytics platform that helps you maximize value from your data and is designed to be multi-engine, multi-format, and multi-cloud.

Store 10 GiB of data and run up to 1 TiB of queries for free per month. New customers also get $300 in free credits to try BigQuery and other Google Cloud products.

Get started for free Contact sales

Features

Power your data agents with Gemini in BigQuery

Gemini in BigQuery provides AI-powered assistive and collaboration features, including code assist, visual data preparation, and intelligent recommendations that help enhance productivity and optimize costs. BigQuery provides a single, unified workspace that includes a SQL, a notebook, and a NL-based canvas interface for 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.

Gemini in BigQuery

Learn how to build data agents with Gemini in BigQuery

Bring multiple engines to a single copy of data

BigQuery has multi-engine capabilities that includes SQL and serverless Apache Spark. A unified metastore for shared runtime metadata provides unified security and governance controls across all engines and storage types, and now supports Apache Iceberg. By bringing multiple engines, including SQL, Spark, and Python to a single copy of data and metadata, you can break down data silos and increase efficiency.

BigQuery unified platform

What's New with BigQuery at Next

Manage all data types and open formats

Use BigQuery to manage all data types across clouds, structured and unstructured, with fine-grained access controls. Support for open table formats gives you the flexibility to use existing open source and legacy tools while getting the benefits of an integrated data platform. BigLake, BigQuery’s storage engine, lets you have a common way to work with data and makes open formats like Apache Iceberg, Delta, and Hudi. Read new research on BigQuery's Evolution toward a Multi-Cloud Lakehouse.

Build a lakehouse with BigQuery

Build an open and fully managed lakehouse with BigQuery at Next

Built-in machine learning

BigQuery ML provides built-in capabilities to create and run ML models for your BigQuery data. You can leverage a broad range of models for predictions, and access the latest Gemini models to derive insights from all data types and unlock generative AI tasks, such as text summarization, text generation, multimodal embeddings, and vector search. It increases the model development speed by directly bringing ML to your data and eliminating the need to move data from BigQuery.

How to accelerate machine learning with BigQuery ML

Analyze data in BigQuery using Gemini models

Built-in data governance

Data governance is built into BigQuery, including full integration of Dataplex capabilities, such as a unified metadata catalog, data quality, lineage, and profiling. Customers can use rich AI-driven metadata search and discovery capabilities for assets, including dataset schemas, notebooks and reports, public and commercial dataset listings, and more. BigQuery users can also use governance rules to manage policies on BigQuery object tables.

AI and data governance

Data and AI governance at Next

Real-time analytics with streaming data pipelines

Use Managed Service for Apache Kafka to build and run real-time streaming applications. From SQL-based easy streaming with BigQuery continuous queries, popular open-source Kafka platforms, and advanced multimodal data streaming with Dataflow, including support for Iceberg, you can make real-time data and AI a reality.

Enterprise capabilities

BigQuery continues to build new enterprise capabilities. Cross-region disaster recovery provides managed failover in the unlikely event of a regional disaster as well as data backup and recovery features to help you recover from user errors. BigQuery operational health monitoring provides organization-wide views of your BigQuery operational environment. BigQuery Migration Services provides a comprehensive collection of tools for migrating to BigQuery from legacy or cloud data warehouses.

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.

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.

Run sample query

BigQuery product UI

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

Common Uses

Generative AI

Unlock generative AI use cases with BigQuery and Gemini models

Build data pipelines that blend structured data, unstructured data, and generative AI models together to create a new class of analytical applications. BigQuery integrates with Gemini 1.0 Pro using Vertex AI. The Gemini 1.0 Pro model is designed for higher input/output scale and better result quality across a wide range of tasks like text summarization and sentiment analysis. You can now access it using simple SQL statements or BigQuery’s embedded DataFrame API from right inside the BigQuery console.

Learn more about BigQuery and Vertex AI integrations

Generative AI use cases

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

Cloud Data warehouse migration diagram

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

Unlock value from all data types

Derive insights from images, documents, and audio files and combine with structured data

Unstructured data represents a large portion of untapped enterprise data. However, it can be challenging to interpret, making it difficult to extract meaningful insights from it. Leveraging the power of BigLake, you can derive insights from images, documents, and audio files using a broad range of AI models, including Vertex AI’s vision, document processing, and speech-to-text APIs, open-source TensorFlow Hub models, or your own custom models.

Learn more about unstructured data analysis

Google Cloud infrastructure diagram

Pre-configured data solutions

Deploy a preconfigured data warehouse in the Google Cloud console

Deploy an example data warehouse solution to explore, analyze, and visualize data using BigQuery and Looker Studio. Plus, apply generative AI to summarize the results of the analysis.

Deploy in console

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

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 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 logs using BigQuery

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

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 to manage any infrastructure and built-in BI and AI/ML.

Explore more use cases for data clean rooms

Pricing

How BigQuery pricing works	BigQuery pricing is based on compute (analysis), storage, additional services, and data ingestion and extraction. Loading and exporting data are free.
Services and usage	Subscription type	Price (USD)
Free tier	The BigQuery free tier gives customers 10 GiB storage, up to 1 TiB queries free per month, and other resources.	Free
Compute (analysis)	On-demand Generally gives you access to up to 2,000 concurrent slots, shared among all queries in a single project.	Starting at $6.25 per TiB scanned. First 1 TiB per month is free.
	Standard edition Low-cost option for standard SQL analysis	$0.04 per slot hour
	Enterprise edition Supports advanced enterprise analytics	$0.06 per slot hour
	Enterprise Plus edition Supports mission-critical enterprise analytics	$0.10 per slot hour
Storage	Active local storage Based on the uncompressed bytes used in tables or table partitions modified in the last 90 days.	Starting at $0.02 Per GiB. The first 10 GiB is free each month.
	Long-term logical storage Based on the uncompressed bytes used in tables or table partitions modified for 90 consecutive days.	Starting at $0.01 Per GiB. The first 10 GiB is free each month.
	Active physical storage Based on the compressed bytes used in tables or table partitions modified for 90 consecutive days.	Starting at $0.04 Per GiB. The first 10 GiB is free each month.
	Long-term physical storage Based on compressed bytes in tables or partitions that have not been modified for 90 consecutive days.	Starting at $0.02 Per GiB. The first 10 GiB is free each month.
Data ingestion	Batch loading Import table from Cloud Storage	Free When using the shared slot pool
	Streaming inserts You are charged for rows that are successfully inserted. Individual rows are calculated using a 1 KB minimum.	$0.01 per 200 MiB
	BigQuery Storage Write API Data loaded into BigQuery, is subject to BigQuery storage pricing or Cloud Storage pricing.	$0.025 per 1 GiB. The first 2 TiB per month are free.
Data extraction	Batch export Export table data to Cloud Storage.	Free When using the shared slot pool
Data extraction	Streaming reads Use the storage Read API to perform streaming reads of table data.	Starting at $1.10 per TiB read

Learn more about BigQuery pricing. View all pricing details

Pricing calculator

Estimate your monthly BigQuery costs, including region specific pricing and fees.

Estimate your costs

Custom quote

Connect with our sales team to get a custom quote for your organization.

Request a quote

Start your proof of concept

New customers get $300 in free credits to try BigQuery and other Google Cloud products

Get started for free

Try BigQuery sandbox without a credit card

Learn how to locate and query public datasets in BigQuery

Learn how to load data into BigQuery

Learn how to create and use tables in BigQuery

Partners & Integration

Work with a partner with BigQuery expertise

From data ingestion to visualization, many partners have integrated their data solutions with BigQuery. Listed above are partner integrations through Google Cloud Ready - BigQuery.

Visit our partner directory to learn about these BigQuery partners.

FAQ

What makes BigQuery different from other enterprise data warehouse alternatives?

keyboard_arrow_up

BigQuery is Google Cloud’s fully managed and completely serverless enterprise data warehouse. BigQuery supports all data types, works across clouds, and has built-in machine learning and business intelligence, all within a unified platform.

What is an enterprise data warehouse?

keyboard_arrow_down

How secure is BigQuery?

keyboard_arrow_down

How can I get started with BigQuery?

keyboard_arrow_down

What is the BigQuery sandbox?

keyboard_arrow_down

What are the most common ways companies use BigQuery?

keyboard_arrow_down

Other inquiries and support

Billing and troubleshooting Ask the community

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%