EMC releases free edition of Greenplum MPP database

The Community Edition includes free analytical tool set; EMC also announces free version of Alpine Miner data mining software

EMC Tuesday introduced a free Community Edition of the its high-performance, massively parallel Greenplum Database for research and development projects.

The company said that the new Greenplum Database CE offering includes free analytic algorithms and data mining tools.

"This is a product designed to get people started developing on our products and on open source technology," Luke Lonergan, CTO of EMC's Data Computing Products Division. "It's free for research and development. If they go production and want support, then they have to pay license fee, which is per terabyte or PC core."

The Greenplum Database CE business analytics tools allow users to view, modify and enhance included demo data files.

The Community Edition can be downloaded as a pre-configured VMWare virtual appliance for use on laptops and desktops, or as a set of packages for deployment on user machines. All users are free to participate in new Greenplum Community Forums to get support, collaborate, post ideas, and test enhancements developed by various users independently, Lonergan said.

Greenplum CE users can also take advantage of the product's open-source analytic algorithm library, MADlib, to give them data mining and machine-learning methods for structured and unstructured data.

EMC also announced a free version of Alpine Miner, a visual data mining modeler that delivers rapid "modeling to scoring" capabilities, leverages in-database analytics. Alpine Miner is a drag and drop interface with a collection of algorithms that allow users to create models about their data, after extracting it from the database.

For example, Lonergan said, a retailer could use the database to model the value of a customer or set of customers on a particular day or quarter, as well as what they might be worth as a customer if they began purchasing products they currently aren't. In addition, he said, a service provider could determine the probability that a customer might leave for a competitor's product, and then use that information for future interactions with the customer.

"There are a number of other elements we'll also be adding in the future," Lonergan said.

Lucas Mearian covers storage, disaster recovery and business continuity, financial services infrastructure and health care IT for Computerworld. Follow Lucas on Twitter at @lucasmearian, or subscribe to Lucas's RSS feed . His e-mail address is lmearian@computerworld.com.

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