About MapReduce MapReduce is a programming model specifically implemented for processing large data sets. The model was developed by Jeffrey Dean and Sanjay Ghemawat at Google (see “ MapReduce ...

Everyone knows that if MapReduce and Hadoop require elite programmers to write programs to analyze data, then the size of the market will be small. A burning question for all Hadoop vendors is ...

A recent article on the Database Column by David J. DeWitt and Michael Stonebraker attempts to compare the increasingly popular MapReduce programming paradigm to a relational database. The ...

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 ...

Distributed programming models such as MapReduce enable this type of capability, but the technology was not originally designed with enterprise requirements in mind. Now that MapReduce has been ...

Distributed programming models such as MapReduce enable this type of capability, but the technology was not originally designed with enterprise requirements in mind. Now that MapReduce has been ...

MapReduce is emerging as a parallel data processing standard, but often requires extensive learning time and specialized programming skills.

Google introduced the MapReduce algorithm to perform massively parallel processing of very large data sets using clusters of commodity hardware. MapReduce is a core Google technology and key to ...

MapReduce programming will still be required, of course, but SQL support makes the results rapidly accessible to many more people.

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 ...