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Getting a Quick Start With Hadoop

 
 
By Michael Vizard  |  Posted 2015-02-20 Print this article Print
 
 
 
 
 
 
 
big data apps

Although Hadoop represents a major opportunity for solution providers with big data expertise, setting up and configuring a Hadoop cluster can be a significant challenge.

Looking to reduce that task's complexity, MapR Technologies at the Strata + Hadoop World 2015 conference announced three Quick Start Solutions for its distribution of Hadoop.

As part of a move to reduce the time and effort required to deploy Hadoop, MapR Technologies will begin making available preconfigured offerings aimed at specific use cases, said Jack Norris, chief marketing officer for MapR Technologies.

The first three include a Data Warehouse Optimization and Analytics Solution, a Security Log Analytics Solution and a Recommendation Engine Solution that optimizes sales offers in real-time based on customer behavior.

Rather than being dedicated appliances, the Quick Start Solutions (priced staring at $30,000) are designed to provide a customizable application framework that allows solution providers to deliver a Hadoop implementation that starts to return value on that investment a lot faster than building every aspect of the solution from the ground up, Norris said.

While there is a lot of interest and demand for Hadoop, solution providers don't always have access to deep Hadoop expertise. In fact, most customers are not necessarily interested in acquiring Hadoop as much as the capabilities of the applications that run on top of it.

As Hadoop continues to evolve, Norris said, one of things that distinguishes MapR Technologies' Hadoop offering is that it can be deployed as a distributed computing platform capable of supporting both in-memory and batch-mode applications that go well beyond analytics. In contrast, other distributions of Hadoop are optimized for analytics applications running on a single Hadoop cluster, he added.

The latest version of MapR Technologies' Hadoop distribution, for example, added expanded support for table replication between different instances of Hadoop.

That capability may be fine for some applications, but given that most organizations don't know in what direction their future Hadoop application requirements will need to scale, standardizing on the distribution of Hadoop from MapR Technologies is the smarter long-term bet, Norris said.

It's still early days when it comes to all things Hadoop. But one thing that is for certain is that the distribution of Hadoop that makes it simplest to first derive value and then be extensible into new application areas is going to get a fair amount of attention across the channel.

Michael Vizard has been covering IT issues in the enterprise for 25 years as an editor and columnist for publications such as InfoWorld, eWEEK, Baseline, CRN, ComputerWorld and Digital Review.

 
 
 
 
 
 
 
 
 
 

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