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Hortonworks, Concurrent Team Up on Cascading SDK

Hortonworks, Concurrent Team Up on Cascading SDK
By Barry Levine

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"By expanding our alliance with Concurrent and integrating with the Cascading application platform, Hortonworks' customers can now drive even more value from their enterprise data by enabling the rapid development of data-driven applications," said John Kreisa, vice president of marketing at Hortonworks, of the Concurrent partnership.
 



Concurrent and Hortonworks are teaming up to streamline enterprise application development of data-centric applications. The strategic partnership was announced Tuesday.

Concurrent, an enterprise data application platform company, will integrate its Cascading SDK, a widely used application development framework for Hadoop-based data applications, with Hortonworks Data Platform. Hortonworks, a provider of enterprise-targeted Apache Hadoop, will certify, support and deliver Cascading.

Hortonworks said it will also guarantee the ongoing compatibility of Cascading-based applications with future releases of the Hortonworks Data Platform, through continuous testing for compatibility and direct customer support.

Apache Tez

Cascading, in a future release, is expected to support Apache Tez, which will allow projects to accommodate faster response times and near real-time data processing. Companies that are using Cascading, Lingual, Scalding, or other dynamic programming language APIs and frameworks will now have the ability to migrate to new releases of the data platform that support Apache Tez.

On its Web site, Hortonworks said Apache Tez allowed "projects in the Apache Hadoop ecosystem...to meet demands for fast response times and extreme throughput at petabyte scale."

John Kreisa, vice president of strategic marketing at Hortonworks, said in a statement that, "by expanding our alliance with Concurrent and integrating with the Cascading application platform, Hortonworks' customers can now drive even more value from their enterprise data by enabling the rapid development of data-driven applications."

Cascading is open-source software that is employed for the development and implementation of complex data processing workflows on Hadoop, thereby providing an abstracted and higher level control over MapReduce processing, which is the data processing backbone in Hadoop. It offers a computation engine, systems integration framework, data processing and scheduling. Concurrent's services include commercial support for Cascading, and Cascading was initially created by Chris Wensel, the Concurrent founder.

'A Must-Have'

Also open source, Apache Hadoop is a framework for processing large data sets. It is intended to provide insights into large stores of structured and unstructured data. Hortonworks was founded in 2001 by members of the original Hadoop development and operations team at Yahoo.

"The need for simple, powerful tools for big-data application development is a must-have to survive in today's competitive climate," Concurrent CEO Gary Nakamura told news media.

Hortonworks' alliance with Concurrent is only the latest in a series. Last week, the Palo Alto, Calif.-based Hortonworks announced a new addition to its joint engineering alliance with open-source provider Red Hat. The two companies will integrate Red Hat's platform-as-a-service OpenShift with Hortonworks Data Platform, so that Hadoop can be used in an open hybrid cloud. This follows an announcement in February that the companies will deliver an open-source initiative for delivering Hadoop to the hybrid cloud.

In early April, Hortonworks announced a strategic partnership with Lucidworks, allowing users of Hortonworks Data Platform to access and analyze their data through the open-source enterprise search platform, Solr.

At the beginning of April, Hortonworks released version 2.1 of its data platform. Highlights of the new release included interactive SQL query, improved capabilities for data governance and security, and two new processing engines for streaming and search.
 

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Ed.:

Posted: 2014-04-23 @ 11:25am PT
@Veronica: Thanks for the catch. We made that correction.

Veronica Herico:

Posted: 2014-04-23 @ 10:34am PT
Hello - Just wanted to note a small, but relevant typo, the open source enterprise search platform referenced in the piece is spelled Solr not "Soir".

Best,

Veronica Herico
Eastwick



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