{"id":3670,"date":"2013-03-20T07:00:09","date_gmt":"2013-03-20T15:00:09","guid":{"rendered":"http:\/\/www.formtek.com\/blog\/?p=3670"},"modified":"2013-03-20T07:00:09","modified_gmt":"2013-03-20T15:00:09","slug":"big-data-hadoop-ranks-on-top-but-its-many-challenges-make-it-vulnerable","status":"publish","type":"post","link":"https:\/\/formtek.com\/blog\/big-data-hadoop-ranks-on-top-but-its-many-challenges-make-it-vulnerable\/","title":{"rendered":"Big Data: Hadoop Ranks on Top, but its many Challenges Make it Vulnerable"},"content":{"rendered":"

Hadoop started as a tool intended to jump-start Yahoo’s search engine. \u00a0And over the course of the last ten years, Hadoop has morphed into a general-purpose computing platform, in fact, the go-to platform for all things related to Big Data.<\/p>\n

Hadoop, of course, \u00a0is not the only option for doing Big Data analysis, but it does seem to be pulling away from the other options. \u00a0Chris Preimesberger<\/a>, for example, predicted in eWeek <\/a>that\u00a0“Hadoop will distance itself from MongoDB, Cassandra, Couchbase and the numerous NoSQL options to become the safe choice. In stark contrast to the fractured and niche-oriented nature of the alternatives, Hadoop offers a uniform approach to a broad set of APIs for big data analytics (including MapReduce, query languages and database access, with easy integration of leading analytic and search platforms) along with an expanding ecosystem to deliver a wide range of services.”<\/p>\n

But despite the mindshare that Hadoop has garnered in the world of Big Data, all is not well with Hadoop. \u00a0Hadoop is a complex and challenging platform, one difficult to use productively.<\/p>\n

Paul Barsch<\/a> on Smart Data Collective<\/a>, speculated that “The truth is that some companies are having wild success reporting, analyzing, and predicting on terabytes and in some cases petabytes of Big Data. But for every eBay, Google, or Amazon or Razorfish there are thousands of companies stumbling, bumbling and fumbling through the process of Big Data analytics with little to show for it.”<\/p>\n

With what success are businesses having in their attempts to get Hadoop and Big Data to work for them? \u00a0Today Dimensional Research released<\/a> the findings of a recent survey sponsored by Rainstor<\/a> that investigated how businesses are using Hadoop to solve Big Data problems. \u00a0Of the businesses surveyed that have attempted to use Hadoop, half haven’t gotten past the planning stage, and only about a quarter have managed to see their Hadoop Big-Data projects through to production. \u00a088 percent of companies using Hadoop cited challenges in getting the platform to do what they envisioned.<\/p>\n

The main challenges these businesses named in using Hadoop include:<\/p>\n