Cost, flexibility and the availability of trained personnel are major reasons for the open-source boom. Hadoop, R and NoSQL are now the supporting pillars of many enterprises' big data strategies, whether they involve managing unstructured data or performing complex statistical analyses on it."

It's almost hard to keep up: SAP AG recently released a new product, SAP BusinessObjects Predictive Analysis, software that integrates algorithms from the open-source R language, which is used extensively in the academic community for advanced statistical modelling.

A few weeks before that, Teradata Corp. announced that its new integrated analytics portfolio would include R functionality as well as a connection to GeoServer, a Java-based open-source geolocation platform. Countless other companies are rushing to build links to Hadoop.

Widespread adoption, feverish innovation

James Kobielus, then an analyst at Forrester Research Inc. (he's now senior program director for product marketing of big data analytics solutions at IBM Corp.), wrote in an e-mail message that "open-source approaches have the momentum of the most widespread adoption and the most feverish innovation."