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12 Top Big Data Analytics Players

Doug Henschen October 18, 2011 08:01 AM When data grows into the tens or even hundreds of terabytes, you need a special technology to quickly make sense of it all. From Hadoop to Teradata, check out the top platform options.

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Hadoop And MapReduce Boil Down Really Big Data

Hadoop is a collection of open-source distributed data-processing components for storing and processing structured, semi-structured, or unstructured data at truly high scale (as in tens or hundreds of terabytes of even petabytes). Clickstream and social-media analysis applications are driving much of the demand, and of particular interest is MapReduce, a technique supported by Hadoop (and a few other environments) that is ideal for processing big data sets. MapReduce breaks a big data problem into sub-problems, distributes those onto dozens, hundreds, or even thousands of processing nodes and then combines the results into a smaller data set that's easier to analyze.

Hadoop runs on low-cost commodity hardware and it scales up at a fraction of the cost of commercial storage and data-processing alternatives. That has made it a staple at Internet giants including AOL, eHarmony, eBay, Facebook, Twitter, and Netflix. But even more traditional firms coping with big data, like JPMorgan Chase, are embracing the platform.

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By The Numbers

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

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