Google BigQuery is a web service that lets you do interactive analysis of massive datasets—up to billions of rows. Scalable and easy to use, BigQuery lets developers and businesses tap into powerful data analytics on demand.
The BigQuery service is built on the back of Google’s enormous investments in data infrastructure and exposes some of the clever tools the company has built for internal use to an internal audience. It’s designed to help with ad hoc queries against unstructured data – kind of Hadoop in the cloud with a front-end querying service attached. In this regard it shares some similarities with the Hadoop on Azure service from my illustrious employers.
The interesting question with all these cloud-based Big Data services (a list of some of which you can find here, and here) is the acceptability to customers of loading significant amounts of data to the cloud, and dealing with the privacy and security questions that arise as a result. But it is interesting to contrast the significant complexity that attends any conversation about in-house or on-premise big data with the simplicity offered by a cloud-based approach.
The most intriguing aspect of Google’s foray into this area is the prospect of the company being able to leverage its “secret sauce” in terms of data analysis tools and technologies – few other companies may be able to match the kind of investment that Google can make here.