Hortonworks’ business model hasn’t changed “one bit” since it spun off from Yahoo in 2011, according to company president Herb Cunitz. Speaking at SiliconANGLE’s recently concluded Big Data New York 2013 summit, Cunitz tells theCUBE hosts John Furrier and Dave Vellante that his firm is committed to delivering an open analytics stack for the enterprise.

Hortonworks is helping organizations unlock the value of information with Hadoop, a freely available batch processing framework distributed under the Apache license. An open community can “out innovate any individual company” given sufficient resources, Cunitz says, which is one of the reasons the platform is poised to become an industry standard for analytics.

To establish Hadoop as a full-fledged Big Data operating system, Hortonworks offers a homegrown version with a number of enterprise capabilities that are not included in the vanilla release. The startup also collaborates with big name vendors such as SAP and Microsoft to make Hadoop compatible with legacy systems, and provides complementary services that aim to bridge the Big Data skill gaps in traditional enterprises.

Cunitz reveals that 70 percent of Hortonworks’ revenue is generated from support subscriptions, while 30 percent is accounted by training and consultancy. He hopes to achieve an 80-20 ratio as the startup’s customer base grows and the open source market continues to evolve.

“The market conditions are different now than they were even 5 years ago to allow a pure open source company to prosper,” Cunitz says. “Think about the maturity of open source in the market and how it’s used today: companies are comfortable using and betting their business on it where they may not have been 10 years ago. The legal requirements have been pushed through, the idea of a subscription model is not foreign to companies anymore.”

Getting back to Hadoop, Cunitz highlights that HDP 2.0, the latest release of Hortonworks’ flagship distribution, utilizes YARN to extend the platform beyond batch analytics. Users can now run SQL-like queries against historical data and process fast-moving information streams on-the-fly in one place.

Check the video below for the full interview.