Aster Data is providing customers with more than 1,000 new MapReduce-ready features designed to increase the adoption of MapReduce by enterprises dealing with big data applications.
Aster Data hopes to increase the adoption of MapReduce by enterprises
dealing with big-data
With Aster Data Analytical Function 4.5, the company is delivering more than
"30 business-ready advanced analytic packages and more than 1,000
MapReduce-ready functions" available for Aster Data nCluster 4.5 and
above. The goal, the company said June 21, is to "enable rapid development
of rich analytic applications on big data."
"We're very focused on being able to make MapReduce as a programming
framework and support its broad adoption for big data analysis in today's
enterprises," said Stephanie McReynolds, director of product marketing at
Aster Data. "One of the mechanisms we have to support that rapid adoption
is introducing out-of-the-box, ready-to-use prepackaged functions."
The new functions "cover a wide range of advanced analytic use cases,"
including graph, text and cluster analysis. Aster Data has coupled SQL with
MapReduce so users do not "need to learn MapReduce programming or parallel
programming concepts" and can build advanced applications that can be
accessed through simple SQL statements.
"About 75 percent of the time spent on data mining projects can be
spent on preparing data for analysis, just to get the data into a usable
state," IDC analyst Dan Vesset said in
a statement. "Aster Data's new approach to analytic application processing
improves performance and scalability for data-driven applications and
exploratory analysis of big data, which is becoming increasingly important to
organizations as a means to create competitive advantage."