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BigQuery

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Google BigQuery enables companies to handle large amounts of data without having to manage infrastructure. Google’s documentation describes it as a « serverless architecture (that) lets you use SQL queries to answer your organization’s biggest questions with zero infrastructure management. BigQuery’s scalable, distributed analysis engine lets you query terabytes in seconds and petabytes in minutes. » Its client libraries allow the use of widely known languages such as Python, Java, JavaScript, and Go. Federated queries are also supported, making it flexible to read data from external sources.

📖 A highly rated canonical book on it is « Google BigQuery: The Definitive Guide », a comprehensive reference.

Another enriching read on the subject is the inside story told in the article by the founding product manager of BigQuery celebrating its 10th anniversary.

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Give AI agents the context to query business data correctly through the open context layer that gives AI agents grounded, governed memory, context, SQL across 20+ data sources, that helps you build GenBI, agentic BI, text-to-sql, dashboards, and agentic analytics.

  • Updated May 29, 2026
  • Python

Released May 19, 2010

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Repository
GoogleCloudPlatform/bigquery-utils
Website
github.com/topics/bigquery
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cloud-computing