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February 1, 2012

Karmasphere Makes Hadoop Work Overtime

Datanami Staff

It seems like just yesterday that big data analytics startup Karmasphere was securing its second round of funding and announcing some primo new partnerships with the “big dogs” in the Hadoop ecosystem, including with the leading Hadoop distro spinners, Cloudera, Hortonworks, and MapR.

The company, which focuses on bringing the power of Hadoop to more users via familiar backend and graphical tools, got its start in 2005, well ahead of the Hadoop hoopla—and has since gone on to persist in valuable partnerships and additions to its Karmasphere Analyst and Karmasphere Studio products.

This week the Cupertino-based company announced the newest release of its Karmasphere Analyst that is set to make Hadoop work a bit of overtime for data analysts in need of multiple queries.  To this end, a statement from today says the version 1.8 release introduces two “firsts” in the Hadoop and Hive ecosystems; parallel and parameterized queries.

According to Karmasphere, the updated version of Analyst offers a parallel query capability that they say will make it faster for data analysts to iteratively query their data and create visualizations. The company claims that the new update allows data analysts to submit queries, view results, submit a new set and then compare those results across the previous outputs. In essence, this means users can run an unlimited number of queries concurrently on Hadoop so that one or more data sets can be viewed while the others are being generated.

Karmasphere also says that the introduction of parameterized queries allows users to submit their queries as they go, while offering them output in easy-to-read graphical representations of the findings, in Excel spreadsheets, or across a number of other outside reporting tools.

According to Rich Guth, Karmasphere’s CMO, “We are seeing big data analytics teams consisting of one or more data analyst ‘power users’…this allows these data analysts and the business people they support to pull value out of their big data without running into technological roadblocks or taking too long to get the results.”

In addition to these two workflow-oriented updates to Karmasphere, the company has also added support for HBase to allow for more efficient read/write action on multi-structured data as well as support for the latest Hive release (0.7.1).

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