Briefs

Speed, efficiency of parallel SQL databases superior, paper shows

By Eric Lai, April 13, 2009 (Computerworld) A team of researchers will release on Tuesday a paper showing that parallel SQL databases perform up to 6.5 times faster than Google Inc.'s MapReduce data-crunching technology.

Google bypassed parallel databases and invented MapReduce as a way to index the World Wide Web on its global grid of low-end PC servers. As of January 2008, Google has used MapReduce to process 20 petabytes of data a day.

In results of in-house tests published last November, Google used MapReduce running on 1,000 servers to sort 1TB of data in just 68 seconds.

Microsoft technical fellow David DeWitt and Michael Stonebraker, a database industry legend and chief technology officer at Vertica Systems Inc., who co-authored the paper, have previously argued that MapReduce lacks many key features already standard to databases and was generally a "major step backward."

Here is their paper "A Comparison of Approaches to Large-Scale Data Analysis,".