Low Cost, Better Analysis Cited as Top Hadoop Attributes: Survey

First, the good news: a significant number of organizations have some sort of Hadoop project in production, with a sizable percentage using the open-source framework to crunch more than 500 TB of data.

The bad news: 88 percent of those organizations using Hadoop are facing challenges with regard to actual implementation.

Those were the conclusions drawn from a recent survey conducted by Dimensional Research and sponsored by RainStor. Out of 107 respondents, 24 percent indicated they had a Hadoop project in production, while 19 percent indicated they managed more than 500 TB of data with Hadoop.

Some 53 percent of those interviewed opted for Hadoop because of its low cost to scale; around 44 percent said they chose it because of its “better analysis”; and 32 percent claimed the framework’s “unique functionality” drew them in.

Out of the various Hadoop query methods, some 68 percent indicated they used Hive, while 57 percent said MapReduce; another 34 percent went with Pig, and 15 percent opted for Native SQL. Many of these companies are obviously relying on more than one method for their data-crunching needs.

But these organizations also seemed to face multiple challenges in terms of their Hadoop analytics work. Some 37 percent complained that Hadoop wasn’t “real time”; another 26 percent were concerned about the time needed to put their Hadoop platform into production. Nearly as many—25 percent—indicated manual coding as a challenge, while 18 percent thought that the cost of training and services was a significant hurdle. “Other” challenges constituted 15 percent of responses, and 12 percent said they faced no issues.

More and more IT vendors—from EMC and Hortonworks to Cloudera and many others—have recently issued additions to their respective Hadoop offerings, seeking to capitalize on the interest in the framework. Indeed, research firm IDC has suggested that Hadoop will remain popular for some time to come, with estimated earnings of $812.8 million by 2016 (other research firms estimate those revenues much higher).

There is the possibility, of course, that all this interest in Hadoop could lead to a bubble of some sort.

 

Image: Big Data and Hadoop report

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