BigQuery
Cloud-based data warehouse service
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Through Google, Analysis and Cloud computing
History
BigQuery originated from Google's internal Dremel technology, which enabled quick queries across trillions of rows of data. The product was originally announced in May 2010 at Google I/O. Initially, it was only usable by a limited number of external early adopters due to limitations on the API. However, after the product proved its potential, it was released for limited availability in 2011 and general availability in 2012. After general availability, BigQuery found success among a broad range of customers, including airlines, insurance, and retail organizations.
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Design
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 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.
- Integration - BigQuery can be used from Google Apps Script (e.g. as a bound script in Google Docs), or any language that can work with its REST API or client libraries.
- Access control - Share datasets with arbitrary individuals, groups, or the world.
- Machine learning - Create and execute machine learning models using SQL queries.