Aster Data Pushes MapReduce for Enterprises

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 applications.

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."