Announced at GigaOm Structure Data event, Google launches a new BigData service named BigQuery:
BigQuery enables businesses and developers to gain real-time business insights from massive amounts of data without any upfront hardware or software investments.
A quick bullet point list of BigQuery features and limitations:
- BigQuery is ideal for running queries over vast amounts of data—up to billions of rows—with great speed.
- BigQuery is good for analyzing vast quantities of data quickly, but not for modifying it. In data analysis terms, BigQuery is an OLAP (online analytical processing) system.
- You can import data into BigQuery as CSV data, where it is stored in the cloud in a relatively small number of tables with no explicit relationship to each other.
- BigQuery isn’t a database system:
- It doesn’t support table indexes or other database management features.
- BigQuery supports a specialized subset of SQL; it doesn’t support update or delete requests.
- BigQuery supports joins only when one side of the join is much smaller than the other.
- BigQuery can be used by any client able to send REST commands over the Internet.
After the break you can watch the 15 minutes video recorded at the GigaOm event.
- Google BigQuery
- GigaOm: Google opens up its BigQuery data analytics service to all
- Bits NYTimes: Google Offers Big-Data Analytics
Original title and link: Google BigQuery: Running SQL-like Queries Against Very Large Datasets ( ©myNoSQL)