Google and its MapReduce framework may rule the roost when it comes to massive-scale data processing, but there’s still plenty of that goodness to go around. This article gets you started with Hadoop, ...

MapReduce was invented by Google in 2004, made into the Hadoop open source project by Yahoo! in 2007, and now is being used increasingly as a massively parallel data processing engine for Big Data.

Two Google Fellows just published a paper in the latest issue of Communications of the ACM about MapReduce, the parallel programming model used to process more than 20 petabytes of data every day on ...

Hadoop has been widely embraced for its ability to economically store and analyze large data sets. Using parallel computing techniques like MapReduce, Hadoop can reduce long computation times to hours ...

I gave an introductory talk on Hadoop yesterday at the Visual Studio Live! conference in Las Vegas. During the talk, I discussed how Hadoop Streaming, a utility which allows arbitrary executables to ...

Reporting and analysis tools help businesses make better quality decisions faster. The source of information that enables these decisions is data. There are broadly two types of data: structured and ...

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On the eve of another Strata week, EMC Greenplum announced Pivotal HD, a Hadoop distribution that is tightly integrated with an MPP database engine called HAWQ. What all this alphabet soup means is ...

Release 15.4 of the analytic database will feature support for the MapReduce and Hadoop programming frameworks for large-scale data processing Sybase is hoping its IQ analytic database can make its ...

The market for software related to the Hadoop and MapReduce programming frameworks for large-scale data analysis will jump from US$77 million in 2011 to $812.8 million in 2016, a compound annual ...