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BigQuery provides external access to the Dremel technology, a scalable, interactive ad hoc query system for analysis of read-only nested data. To use the data in BigQuery, it first must be uploaded to Google Storage and in a second step imported using the BigQuery HTTP API. 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.