Will Cloudera’s new CEO get down with Hadoop?

Virginia Backaitis
3 min readAug 1, 2019
Tom Reilly no longer rules the roost at Cloudera

Editor’s note: This article is a repost from August 2018 when Tom Reilly was Cloudera’s CEO and its co-founder Mike Olson was its Chief Strategy Officer. Neither of these men remain at the company.

When Cloudera held its quarterly conference call with investors in June of 2018, Deutsche Bank analyst Karl Keirstead presented company CEO Tom Reilly and co-founder, Mike Olson, with an interesting question:

“When I go to Cloudera’s website, I don’t even see the world Hadoop anymore. When I listen to this earnings call, I don’t hear it anymore, and I’m just wondering whether the pivot that Tom (Reilly, Cloudera CEO) laid out at the beginning of the call where you are moving to more ML (machine learning,) analytics and cloud. I’m just wondering does that sort of motivate you to pivot even faster away from those core Hadoop elements to either more Cloudera proprietary IP or perhaps different open source software, whether these shifts Tom talked about are almost forcing an accelerated shift away from those core Hadoop roots?”

You can’t blame Keirstead for wanting clarification given that Cloudera had made its name as one of the leading, if not the leading, Hadoop evangelists, that Hadoop “inventor” Doug Cutting is one of Cloudera’s best-known employees, and that Cloudera (together with O’Reilly) sponsored Hadoop’s biggest conference, Strata Hadoop World for almost a decade. (The conference’s name was changed to Strata Data Conference last year.)

Olson provided Keirstead with a thoughtful response:

Look, we are in no way ashamed of Hadoop. It is still a core foundation element of our platform. But those projects, HCF, [inaudible] scale our storage system, not reduce the scale of our processing engine, they were all we had 10 years ago when we started the company.

Today we’ve got a rich suite of analytic engines and power for our distributed query and Spark for receiving processing and model training and so on. We’ve got a rich collection of storage technologies, not just HDFS but on Amazon S3 native storage, on Microsoft ADLS native storage, even IoT native storage for workloads that demand that in the Apache Kudu project. So it’s just a much more interesting platform than before.