Making big data easier yields $10M for Hadoop startup Concurrent

Making big data easier yields $10M for Hadoop startup Concurrent

Jordan Novet, VentureBeat
June 2, 2014

Big data startup Concurrent proves that it pays to make hard computing simpler.

Concurrent founder Chris Wensel devised the open-source Cascading framework for abstracting away the complexities of running MapReduce jobs on the open-source Hadoop big data software for storing and processing lots of different kinds of data.

Now Concurrent has landed $10 million in new funding.

The startup aims to help more companies achieve “pure innovation through data” just as Twitter, the Climate Corp., and others have, chief executive Gary Nakamura said in an interview with VentureBeat.

It ordinarily takes special training to use Hadoop, but Concurrent makes Hadoop more accessible, and thus it becomes easier to write applications that use the magic data sitting in Hadoop.

“There’s ton of innovation around this notion of data and how to crete data products that end users will consume,” Nakamura said.

The company’s new backing is the latest evidence of a trend to make Hadoop more intuitive. Previously, we’ve seen Trifacta do well for itself by cleaning up data in Hadoop; we’ve seen Platfora make strides by constructing full-featured business-intelligence software for data in Hadoop; and we recently saw Splice Machine pull in more funding in its quest to make Hadoop better suited for real-time workloads.

And, of course, Hadoop distribution vendors Cloudera and Hortonworks have brought in big funding rounds recently, the kind of money that could help Hadoop become even more widely used at the largest companies in the world.

Bain Capital Ventures led Concurrent’s new funding round. Rembrandt Ventures and True Ventures also participated.

San Francisco-based Concurrent started in 2008. It has raised $14.95 million to date, including the $4 million round from last year. That’s when Nakamura came aboard.

The startup employs 20 people now, and that figure should double in a year, Nakamura said.

Most of the new money will go toward research and development, although some is being kept aside to pay for people who can win Concurrent new customers — likely the kinds of businesses that already use Cascading heavily.

As of now, Nakamura said, Concurrent has fewer than 10 paying customers. Then again, the company’s first commercial product, the Driven tool for managing and monitoring Cascading applications, came out just four months ago. And more than 7,000 companies use Cascading, Nakamura said. Big opportunities could lie ahead, then.

That could be especially true if Concurrent makes Driven compatible with big data technologies other than MapReduce — like the Tez framework for Hadoop, the open-source Spark engine, and the Storm stream-processing system.

“There’s a lot on the roadmap along the lines of Driven that we have yet to build,” Nakamura said.