Smith says that for organizations that take a progressive, scientific approach to big data analysis, open-source technologies are a natural choice. "Those companies that have a bit of a culture around data science, around exploration and curiousity with data, have really gravitated towards open-source technologies because they're so flexible and they lend themselves to these different ways of just thinking about working with data and exploring different things you can do with that."

Scott Gnau, president of Teradata Labs, which has partnered with Revolution Analytics, says large enterprises will benefit most from commercial packages of open-source technology so they can keep their focus on their particular line of business.

"There is a lot of value to be created in adopting some of the newer technologies that are developed in a Hadoop and MapReduce environment, but to deploy them as an enterprise-class kind of software, where there's dependable version control, and there's dependable scalability and there's support available.

"It's got to be packaged and dependable to get into the mainstream because the mainstream doesn't want to be a software development house," he says.

Will Davis, product marketing manager at EMC Greenplum, agrees. Larger companies, he says, need more stable, reliable incarnations of open-source big data platforms, whether they add the polish themselves or rely on others to do it for them.