Type of site | Platform as a service data warehouse |
|---|---|
| Available in | English |
| Owner | |
| URL | cloud |
| Registration | Required |
| Launched | May 19, 2010 |
| Current status | Active |
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]
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Transcription
Design
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
- 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
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
BigQuery partners and natively integrates with several tools:[15]
- BI and data visualization: Tableau, Microstrategy, ThoughtSpot, SAS, Qlik Neo4j and Dataiku
- Connectors and developer tools: CData, Progress, Magnitude, KingswaySoft, ZapppySys
Adoption
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
- ^ Iain Thomson (November 14, 2011). "Google opens BigQuery for cloud analytics: Dangles free trial to lure doubters". The Register. Retrieved August 26, 2016.
- ^ 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).
- ^ Kazunori Sato (2012). "An Inside Look at Google BigQuery" (PDF). Retrieved August 26, 2016.
- ^ "SQL Reference". Retrieved 26 June 2017.
- ^ "Quota Policy". Retrieved 26 June 2017.
- ^ "BigQuery Service | Apps Script | Google Developers". March 15, 2018. Retrieved April 23, 2018.
- ^ "BigQuery Client Libraries". Retrieved 26 June 2017.
- ^ "bigquery".[permanent dead link]
- ^ "Google Clouds BiqQuery Omni Now Generally Available". 12 October 2021.
- ^ "Analytics Hub".
- ^ "BI Engine".
- ^ "With Many Updates in BigQuery". 2 July 2022.
- ^ "with Many Updates in BigQuery". 2 July 2022.
- ^ "BigQuery Costs". 13 July 2023.
- ^ "BigQuery Section".
- ^ "Customers for Data Analytics".
- ^ "Whats Changed 2021 Gartner Magic Quadrant for Cloud Database Management Systems". 13 January 2022.
- ^ "BigQuery named leader in forrester wave cloud data warehouse". 30 March 2021.
- ^ "Economic Validation Google BigQuery va. Cloud Based EDWS" (PDF).
External links
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This page was last edited on 20 March 2024, at 05:47