The solution is a massively parallel database with an integrated analytics engine that leverages the MapReduce framework for large-scale data processing and couples SQL with MapReduce.

With growth in unstructured big data, RDBMS is inadequate for big data analytics. Know how to use SQL and MapReduce for big data analytics, instead.

DUBLIN, Calif., Nov. 1, 2011 /PRNewswire/ — Sybase, Inc., an SAP® company (NYSE: SAP) and industry leader in enterprise and mobile software, today launched the new version of the Sybase® IQ high ...

Spotting Big Data trends, without MapReduce As Trendspottr shows us, sometimes hardcore algorithms, even older ones, provide new breakthroughs. Written by Andrew Brust, Contributor June 4, 2012 at ...

In what could best be termed a photo finish, Greenplum and Aster Data Systems have both announced that they have integrated MapReduce into their massively parallel processing database engines.

Hadoop MapReduce has been widely embraced for analyzing large, static data sets. New technology integrates a stand-alone MapReduce engine into an in-memory data grid, enabling real-time analytics on ...

Reader, let me introduce you to Big Data. Big Data, meet Reader. Actually, there's a bit more to it than that. Big Data systems involve a wide range of technologies that can only be understood when ...

Sensing a growing interest in big data-style analysis, software provider Revolution Analytics has updated its flagship package of R statistical functions so it can be run with the Hadoop data ...