Andrew C. Oliver

About the Author Andrew C. Oliver


Hadoop, in trouble? Only in Gartner-land

There are lies, damn lies … and technology industry studies.

Back in May, Gartner released a survey that crapped all over the Hadoop industry: Of the 284 CIOs polled by Gartner, only 26 percent claimed to be “either deploying, piloting, or experimenting with Hadoop.” Even with the small sample size and large margin of error, these were depressing numbers — ones that contradicted the level of adoption people like me are seeing in the real world.

Well, Gartner has been wrong before. Released today, a new survey commissioned by AtScale that surveyed more than 2,100 people offers results a whole lot closer to what those of us in the field encounter. Most dramatically, 76 percent of respondents said they plan to use Hadoop — or are already using it and plan to use it more.

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How Apache Ranger and Chuck Norris help secure Hadoop

The Hadoop security project called Ranger supposedly was named in tribute to Chuck Norris in his “Walker, Texas Ranger” role. The project has its roots in XA Secure, which was acquired by Hortonworks, then renamed to Argus before settling in at the Apache Software Foundation as Ranger.

When Hadoop started, it was a set of loosely coupled parts primarily used in the back end of the big Internet companies like Yahoo. These parts were wrapped into distributions and marketed as Hadoop by the likes of MapR, Cloudera, and Hortonworks.

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Big data, big challenges: Hadoop in the enterprise

As I work with larger enterprise clients, a few Hadoop themes have emerged. A common one is that most companies seem to be trying to avoid the pain they experienced in the heyday of JavaEE, SOA, and .Net — as well as that terrible time when every department had to have its own portal.

To this end, they’re trying to centralize Hadoop, in the way that many companies attempt to do with RDBMS or storage. Although you wouldn’t use Hadoop for the same stuff you’d use an RDBMS for, Hadoop has many advantages over the RDBMS in terms of manageability. The row-store RDBMS paradigm (that is, Oracle) has inherent scalability limits, so when you attempt to create one big instance or RAC cluster to serve all, you end up serving none. With Hadoop, you have more ability to pool compute resources and dish them out.

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