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May 06, 2014

Splunk Presents Hunk 6.1

Splunk Inc’s Hunk 6.1 has been rolled out, making it easier for users to transform raw, unstructured data in Hadoop and NoSQL data stores into business insights.

With the new Hunk 6.1, users are at ease to build and share powerful interactive dashboards with charting overlay, pan-and-zoom controls and in-dashboard drill downs. They can also improve security for shared Hadoop clusters by defining roles and queues, with pass through authentication of security credentials from Hunk to users Hadoop clusters.

According to the company, the new Hunk 6.1 covers the power of Hunk outside Hadoop through streaming resource libraries for NoSQL and other data stores such as Apache Accumulo, Apache Cassandra MongoDB and Neo4j. The new Hunk 6.1 announcement encompasses the power of exploratory analytics to additional file formats and data stores. Uses can easily automate access to many file formats, including: texts, sequence files, RCFile, optimized row columnar (ORC) files and Parquet.

“Hunk brings simplicity to the complex world of analyzing massive volumes of data stored in Hadoop and NoSQL,” said Sanjay Mehta, vice president of product marketing, Splunk (News - Alert).

Mehta said that new version of Hunk is ideal for organizations seeking a faster, easier way to unlock the value from huge amounts of historical data at rest. Alternate approaches require specialized skillsets, fixed schemas, complex programming or moving the data – all of which add up to wasted time and lost opportunity, he added.

Hunk comes with a prevailing environment for developers that help them design big data applications using the languages and frameworks they already use and are familiar with.

Hunk includes a standards-based web framework, documented REST API, Eclipse plug-in and software development kits for C#, Java, JavaScript, Python, PHP and Ruby. Users also have an option to embed any Hunk charts and reports into third-party business applications.

Hunk 6.1 has already been beta tested by Splunk customers and several leading NoSQL vendors.




Edited by Maurice Nagle
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