BigQuery

Summary

BigQuery is a managed, serverless data warehouse product by Google, offering scalable analysis over large quantities of data. It is a Platform as a Service (PaaS) that supports querying using a dialect of SQL. It also has built-in machine learning capabilities. BigQuery was announced in May 2010 and made generally available in November 2011.[1]

BigQuery
Type of site
Platform as a service data warehouse
Available inEnglish
OwnerGoogle
URLcloud.google.com/bigquery
RegistrationRequired
LaunchedMay 19, 2010; 13 years ago (2010-05-19)
Current statusActive

Design edit

BigQuery provides external access to Google's Dremel technology,[2][3] a scalable, interactive ad hoc query system for analysis of nested data. BigQuery requires all requests to be authenticated, supporting a number of Google-proprietary mechanisms as well as OAuth.

Features edit

  • Managing data - Create and delete objects such as tables, views, and user defined functions. Import data from Google Storage in formats such as CSV, Parquet, Avro or JSON.
  • Query - Queries are expressed in a SQL dialect[4] 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.[5]
  • Integration - BigQuery can be used from Google Apps Script[6] (e.g. as a bound script in Google Docs), or any language that can work with its REST API or client libraries.[7]
  • Access control - Share datasets with arbitrary individuals, groups, or the world.
  • Machine learning - Create and execute machine learning models using SQL queries.
  • Cross-cloud analytics - Analyze data across Google Cloud, Amazon Web Services, and Microsoft Azure[8][9]
  • Data sharing - Exchange data and analytics assets across organizational boundaries.[10]
  • In-Memory analysis service - BI Engine built into BigQuery that enables users to analyze large and complex datasets interactively with sub-second query response time and high concurrency.[11][12]
  • Business intelligence - Visualize data from BigQuery by importing into Data Studio, a data visualization tool [13]

Pricing edit

The two main components of BigQuery pricing are the cost to process queries and the cost to store data. BigQuery offers two types of pricing - on demand pricing which charges for the number of petabytes processed for each query and flat-rate pricing which charges for slots or virtual CPUs.[14]

Partnerships & integrations edit

BigQuery partners and natively integrates with several tools:[15]

Adoption edit

Customers of BigQuery include 20th Century Fox, American Eagle Outfitters, HSBC, CNA Insurance, Asahi Group, ATB Financial, Athena, The Home Depot, Wayfair, Carrefour, Oscar Health, and several others.[16] Gartner named Google as a Leader in the 2021 Magic Quadrant™ for Cloud Database Management Systems.[17] BigQuery is also named a Leader in The 2021 Forrester Wave: Cloud Data Warehouse.[18] According to a study by Enterprise Strategy Group, BigQuery saves up to 27% in total cost of ownership over three years compared to other cloud data warehousing solutions.[19]

References edit

  1. ^ Iain Thomson (November 14, 2011). "Google opens BigQuery for cloud analytics: Dangles free trial to lure doubters". The Register. Retrieved August 26, 2016.
  2. ^ 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).
  3. ^ Kazunori Sato (2012). "An Inside Look at Google BigQuery" (PDF). Retrieved August 26, 2016.
  4. ^ "SQL Reference". Retrieved 26 June 2017.
  5. ^ "Quota Policy". Retrieved 26 June 2017.
  6. ^ "BigQuery Service | Apps Script | Google Developers". March 15, 2018. Retrieved April 23, 2018.
  7. ^ "BigQuery Client Libraries". Retrieved 26 June 2017.
  8. ^ "bigquery".[permanent dead link]
  9. ^ "Google Clouds BiqQuery Omni Now Generally Available". 12 October 2021.
  10. ^ "Analytics Hub".
  11. ^ "BI Engine".
  12. ^ "With Many Updates in BigQuery". 2 July 2022.
  13. ^ "with Many Updates in BigQuery". 2 July 2022.
  14. ^ "BigQuery Costs". 13 July 2023.
  15. ^ "BigQuery Section".
  16. ^ "Customers for Data Analytics".
  17. ^ "Whats Changed 2021 Gartner Magic Quadrant for Cloud Database Management Systems". 13 January 2022.
  18. ^ "BigQuery named leader in forrester wave cloud data warehouse". 30 March 2021.
  19. ^ "Economic Validation Google BigQuery va. Cloud Based EDWS" (PDF).

External links edit

  • Official website