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Type of site
Software as a service data warehouse
Available inEnglish
LaunchedMay 19, 2010; 10 years ago (2010-05-19)
Current statusActive

BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is a serverless Software as a Service (SaaS) that supports querying using ANSI SQL. It also has built-in machine learning capabilities.


After a limited testing period in 2010, BigQuery was generally available in November 2011 at the Google Atmosphere conference.[1]

In April 2016, European users of the service suffered a 12-hour outage.[2] In May 2016, support was announced for Google Sheets.[3]


BigQuery provides external access to the Dremel technology,[4][5] a scalable, interactive ad hoc query system for analysis of read-only nested data. BigQuery requires all requests to be authenticated, supporting a number of Google-proprietary mechanisms as well as OAuth.


  • Managing data - create and delete tables based on a JSON-encoded schema, import data encoded as CSV or JSON from Google Storage.
  • Query - the queries are expressed in a standard SQL dialect[6] and the results are returned in JSON with a maximum reply length of approximately 128 MB, or an unlimited size when large query results are enabled.[7]
  • Integration - BigQuery can be used from Google Apps Script[8] (e.g. as a bound script in Google Docs), or any language that can work with its REST API or client libraries[9].
  • Access control - is possible to share datasets with arbitrary individuals, groups, or the world.
  • Machine learning


  1. ^ Iain Thomson (November 14, 2011). "Google opens BigQuery for cloud analytics: Dangles free trial to lure doubters". Retrieved August 26, 2016.
  2. ^ Simon Sharwood (April 7, 2016). "Google Euro-cloud glitch". Retrieved August 26, 2016.
  3. ^ Jordan Novet (May 6, 2016). "Google BigQuery now lets you analyze data from Google Sheets". Retrieved August 26, 2016.
  4. ^ Sergey Melnik; Andrey Gubarev; Jing Jing Long; Geoffrey Romer; Shiva Shivakumar; Matt Tolton; Theo Vassilakis (2010). "Dremel: Interactive Analysis of Web-Scale Datasets". Proc. of the 36th International Conference on Very Large Data Bases (VLDB).
  5. ^ Kazunori Sato (2012). "An Inside Look at Google BigQuery" (PDF). Google. Retrieved August 26, 2016.
  6. ^ "SQL Reference". Retrieved 26 June 2017.
  7. ^ "Quota Policy". Retrieved 26 June 2017.
  8. ^ "BigQuery Service | Apps Script | Google Developers". March 15, 2018. Retrieved April 23, 2018.
  9. ^ "BigQuery Client Libraries". Retrieved 26 June 2017.

External links[edit]