Google BigQuery

04 Sep 2012 by

Google designed BigQuery as a cloud service for running fast queries against massive datasets, but with lofty ambitions there’s always room to take a step back. Now, users that don’t require super speed can run batch queries, and can connect to the service using Microsoft Excel.

For more information please visit official page: https://developers.google.com/bigquery/

Google BigQuery Service allows you to run SQL-like queries against very large datasets, with potentially billions of rows. This can be your own data, or data that someone else has shared for you. BigQuery works best for interactive analysis of very large datasets, typically using a small number of very large, append-only tables. For more traditional relational database scenarios, you might consider using Google Cloud SQL instead. You can use BigQuery through a web UI called the BigQuery browser tool, the bq command-line tool, or by making calls to the REST API using various client libraries in multiple languages, such as Java, Python, etc.

Features

BigQuery offers the following features:

  • Speed – Analyze billions of rows in seconds.
  • Scale – Terabytes of data, trillions of records.
  • Simplicity – SQL-like query language, hosted on Google infrastructure.
  • Sharing – Powerful group- and user-based permissions using Google accounts.
  • Security – Secure SSL access.
  • Multiple access methods – Connect to BigQuery using the BigQuery browser, the bq command-line tool, the REST API, or Google Apps Script.

Best Uses

BigQuery is ideal for the following uses:

  • Ad-hoc analysis
  • Standardized reporting
  • Data exploration
  • Web applications

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