Symantec Enterprise Solution for Hadoop Aims to Eliminate Sprawl

Symantec is offering an add-on to its Cluster File System that will allow businesses to run data analytics on existing infrastructure with a minimum of disruption. It utilizes Apache Hadoop, an increasingly popular framework for reliably running distributed applications on large hardware clusters, already in use by a variety of organizations ranging from IBM to Facebook.

Symantec evidently saw a market in companies that want data analytics without the extra management issues involved in overhauling existing infrastructure or adding to storage sprawl. “Our Enterprise Solution for Hadoop helps connect Hadoop’s business analytics to the existing storage environment,” Don Angspatt, vice president of product management for Symantec’s Storage and Availability Management Group, “while addressing key challenges of server sprawl and high availability for critical applications.”

In order words, the system can reduce the required investments in parallel infrastructure, in return shrinking the size of the required storage footprint. With everything in place, organizations will have the ability to scale up to 16 petabytes of structured and unstructured data; analytics will take place wherever the data resides.

Enterprise Solution for Hadoop supports Hortonworks Data Platform (HDP) 1.0 (Hortonworks is Symantec’s Hadoop partner) and Apache Hadoop 1.0.2; it’s available to Cluster File System customers at no charge. A video breaking down how the system works can be found here.

A recent report by Market Research Media estimated that the market for Hadoop will expand at a compound annual growth rate (CAGR) of 58 percent over the next few years, on its way to becoming a $2.2 billion market by 2018.

That’s a significantly higher estimate than the one offered by research firm IDC in May, which placed worldwide revenues from Hadoop-MapReduce ecosystem software at $812.8 million by 2016.

Both Market Research Media and IDC alluded to a tension developing in the space between proprietary and open-source platforms, with revenues ultimately repressed by commercial software vendors lowering product-licensing fees in the face of significant competition from open-source alternatives.

It’s also likely that, as Hadoop gains popularity, storage sprawl among companies with an interest in data analytics; and if that proves the case, expect for more solutions along the lines of Symatic’s to emerge.


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