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Dana Gardner

EMC Greenplum releases Community Edition of MPP database product, big data analysis gets cheaper still

By Dana Gardner | February 8, 2011, 12:04pm PST

Summary: Building on earlier Greenplum “big data” releases, like the EMC Greenplum Data Computing Appliance, the Community Edition lowers the cost barrier to entry for big data power tools for more developers, data scientists, and other data professionals.

EMC recently introduced a free Community Edition of the EMC Greenplum Database, its massively parallel processing (MPP) database, along with free analytic algorithms and data mining tools.

Building on earlier Greenplum “big data” releases, like the EMC Greenplum Data Computing Appliance, the Community Edition lowers the cost barrier to entry for big data power tools for more developers, data scientists, and other data professionals.

The tools help to developers better understand data and provide new data uses, as well provide deeper insights and to better visualize those insights. The release was made at the 2011 O’Reilly Strata Conference, by Scott Yara, vice president, EMC Data Computing Products Division. EMC acquired Greenplum last summer. [Disclosure: Greenplum is a sponsor of BriefingsDirect podcasts.]

With the easily accessible Community Edition stack, developers can build complex applications to collect, analyze and operationalize big data leveraging best of breed big data tools, including the Greenplum Database with its in-database analytic processing capabilities.

“Our new Community Edition provides a parallel-everything ‘big data’ stack with unequaled speed that enables analysts to perform next-generation data analytics and experiment with real-world data, and most importantly — innovate,” explained Luke Lonergan, CTO and vice president, EMC Data Computing Products Division and co-founder of Greenplum. “This project is about empowering developers. They can program using the most popular tools and they have a place to contribute open source extensions to the stack.”

The free EMC Greenplum Community Edition includes:

Greenplum Database CE, an industry-leading MPP database product for large-scale analytics and next-gen data warehousing.
MADlib, an open source analytic algorithms library, providing data-parallel implementations of mathematical, statistical and machine learning methods for structured and unstructured data.
Alpine Miner, an intuitive visual data mining modeler that delivers rapid “modeling to scoring” capabilities, leverages in-database analytics, and is purpose-built for “big data” applications.

Community benefits

The initial release of the Community Edition is designed for both first-time users and experienced Greenplum customers. First-time users gain access to a comprehensive, purpose-built business analytics environment that enables them to view, modify and enhance included demo data files, enabling experimentation with “big data” analytical tools within the Greenplum database. Existing users can download an upgraded version of Greenplum Database CE and analytic tools for integration into their development and research environments.

The Community Edition can be downloaded free of charge from http://community.greenplum.com 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.

Regular Community Edition updates will be made available online. The Community Edition is intended for experimentation, development and research purposes only. Current single-node edition users can deploy the new Community Edition in their single-node production environments. Greenplum commercial licenses must be purchased prior to using code for internal data processing or for any commercial or production purpose.

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Topics

Data Analysis, Greenplum, EMC Corp., Community Edition, Storage, Productivity, Data Mining, Databases, Hardware, Enterprise Software, Software, Data Management, Dana Gardner

Dana Gardner is president and principal analyst at Interarbor Solutions, an enterprise IT analysis, market research, and consulting firm.

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Dana Gardner

Dana Gardner is president and principal analyst at Interarbor Solutions, LLC, a New Hampshire-based IT analysis and new media content production and consultancy firm that he founded in 2005. He produces a series of podcast/videocast/transcript/blog content shows, called BriefingsDirect[tm/sm], some of which are sponsored and which he blogs on. Such sponsored shows are declared individually as such and by what organization or company. When Dana blogs on ZDNet on companies that he does have, or has had, consulting and/or sponsorship relationships, he declares that in each blog entry. There is no connection between the negotiation of such sponsorships and the opinions expressed by Dana here on ZDNet. To date, the following organizations/companies have sponsored, or do sponsor, some BriefingsDirect content, or have consulting relationships with Dana: Active Endpoints Akamai Technologies Aster Data Systems BP Logix Business Technology Quarterly CA Compuware Electric Cloud Genuitec Gerson Lehrman Group Greenplum Hewlett-Packard iTKO JustSystems North America, Inc. Kapow Technologies LogLogic Nexaweb Technologies, Inc. The Open Group Paglo Panda Security Platform Computing Progress Software rPath Sailpoint Splunk TIBCO Software Weblayers Workday WSO2 ZDNet As a matter of CNET Networks and Interarbor Solutions policies, when Dana covers an organization that is also a sponsor of a BriefingsDirect-produced podcast, videocast or any other content, a disclosure will be included with the coverage. Updated (1/4/2010): Instead of providing a disclosure on just those editorials (blog posts, etc.) that intersect the above listed companies, we have changed the policy to include a link to this full disclosure at the end of every one of Dana's blog posts. In the case of audio or video-based coverage, such disclosures will be provided within the editorial content itself.