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Expert Interview (Part 2): Cloudera’s Mike Olson on the Gartner Hype Cycle

At the Cloudera Sessions event in Munich, Germany, Paige Roberts of Syncsort sat down with Mike Olson, Chief Strategy Officer of Cloudera. In the first part of the interview, Mike Olson went into what’s new at Cloudera, how machine learning is evolving, and the adoption of the Cloud in organizations.

In this part he talks about Gartner’s latest hype cycle, and where he sees things going.

Paige:   Did you see the latest Gartner’s hype cycle? They say that Hadoop will be obsolete before it reaches the plateau of productivity.

Mike:    Yes, and I’ll say that Gartner’s conclusions on Big Data just don’t match ours. We’ve got lots of serious customers doing really mission critical production workloads on our platform. I’m not sure who they’re talking to that’s leading to these conclusions. I will say that if you view the Big Data landscape as really just Hadoop, there’s all kinds of reasons to be skeptical, right?

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Especially if you just look at it as MapReduce and HDFS.

That’s right and it’s perfectly fair to say those are awful alternatives to traditional relational databases. In fact, it’s legit to say there’s going to be a place for Oracle, SAP HANA, Teradata, Microsoft SQL Server, and DB2 Parallel Edition for the long term.  Scale out platforms are never going to be good at online transaction processing.

Distributed transactions have been hard forever and nothing about Hadoop makes it easier, but using tools like Impala to do high-performance analytic queries gives companies an alternative for certain parts of their traditional relational workloads on the scale-out platform. We’re not just bullish, we’ve been quite successful in delivering those capabilities to the enterprise.

The Gartner hype cycle, if you look at the terminology, there’s the peak of inflated expectations and then the trough of disillusionment, and then the plateau of productivity. And maybe Gartner’s current down outlook is because right now, we’re in the trough, and it’s the plateau of productivity broadly across the industry we have to get to. We’ve said publicly that we’ve got more than a thousand customers, more than 600 in the Global 8,000 running this platform in production for a bunch of very demanding workloads.

I have to wonder if they’re looking at the Hadoop of 10 years ago, as opposed to now. It used to be you had just MapReduce and HDFS which was really limited, but now it’s 25 different projects including Spark, and all these other capabilities, and that’s a completely different kind of distribution.

Frankly I think that if you look at Hadoop as just Hadoop, then there’s a bunch of stuff it doesn’t do. But the ecosystem has evolved way beyond that.

Yeah, it’s growing all the time. Actually I do, a “What is Hadoop” presentation and it starts with a slide that gives the basics of Hadoop 1.x. “Here’s this cool thing, and let me explain it to you.” Then it shows the ecosystem progressing in slide after slide, now it grew, and it grew, and it grew and grew some more.

HDFS and MapReduce are always going to be part of our platform. They’re really important. But, you can now spin a cluster infrastructure running on Microsoft Azure using ADLS object store and Spark running on top of that and there’s no HDFS or MapReduce anywhere near that thing.

It is no longer the be-all and end-all of Hadoop.

It’s a much more expansive and capable ecosystem than it used to be.

Tune in for the final installment of this interview, where Mike Olson shares his view on women in tech and explains the difference between Cloudera Altus and Director.

Make sure to check out our latest eBook, 6 Key Questions About Getting More from Your Mainframe with Big Data Technologies, and learn what you need to ask yourself to get around the challenges, and reap the promised benefits of your next Big Data project.

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