New York, March 21 -- EMC announced it has acquired Pivotal Labs, a provider of consulting services and application software in an all cash deal. Terms were not announced. The company also announced the release of Greenplum Chorus, a networking and collaboration platform for big data developers and data scientists.
Pivotal Labs is a personalized developer of new Web-based applications, and EMC was once known as storage-oriented company. But with EMC’s acquisition of Greenplum 20 months ago as an entry to the high performance analytics world, the natural fit of Pivotal is to help Greenplum customers extend the reach and usage scenarios for Greenplum’s big data technology.
Scott Yara, SVP of products at Greenplum, speaking at GigaOM’s Structure Data conference in New York, said his company was looking for a way to support its customers in the market for next generation software applications, which he said was “just getting going.”
“That part of just letting Pivotal be Pivotal with the backing of EMC is sort of an exciting play,” said Yara.
EMC plans to invest and expand Pivotal’s reach “on a global scale” and bring the company’s agile consulting services and software to start-ups and global businesses expanding their presence in cloud, big data, social and mobile uses. Pivotal Tracker, the company’s agile project management tool claims to have 240,000 developer customers already.
EMC also announced the release of Greenplum Chorus, a Web-based Facebook-like social toolset for big data, meant to allow data scientists and teams to collaborate on data sets in a social setting.
The new OpenChorus.org initiative coming in the second half of this year will include the release of open source code to accelerate the adoption of collaborative apps running on the Chorus platform.
Will Davis, product marketing at Greenplum, says the platform will support projects applied to Greenplum’s own advances in database technology.
“We’ve been doing a lot of new work on our database and what Chorus brings is the ability for analysts and data scientists to share data to produce insights and make sure their algorithms are coordinating with other projects in a community of data users where everyone is increasing their productivity,” Davis said.
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