Google Cloud BigQuery

Google Cloud Platform (GCP) Serverless, highly scalable, cost-effective data warehouse designed for business agility. Modernize your smart analytics warehouse with BigQuery. Start your free trial today.

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.Google Cloud BigQuery

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.

 

Product highlights

Unified data platform to connect all your data and activate with AI

Built-in machine learning to create and run models using simple SQL

Real-time analytics with streaming and built-in BI

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.Google Cloud BigQuery 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.

Bring multiple engines to a single copy of data

Serverless Apache Spark is available directly in BigQuery. You can write and execute Spark in BigQuery Studio without exporting data or managing infrastructure. Google Cloud BigQuery BigQuery metastore provides shared runtime metadata for SQL and open source engines for a unified set of security and governance controls across all engines and storage types. 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.

 

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. Google Cloud BigQuery 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.

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.Google Cloud BigQuery  It increases the model development speed by directly bringing ML to your data and eliminating the need to move data from BigQuery.

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.

 

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. Google Cloud BigQuery 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.

 

Real-time analytics with streaming data pipelines

BigQuery can ingest streaming data and make it immediately available to query and integrate to streaming products, like Dataflow. Accelerate query performance and reduce costs within BigQuery with materialized views. Google Cloud BigQuery Continuous queries is a new BigQuery feature that unlocks continuous analytical processing through a SQL statement to fuel event-driven applications. Read our latest research on Vortex: A Stream-oriented Storage Engine For Big Data Analytics.

 

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. Google Cloud BigQuery 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.

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.

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.