Concurrent Builds New Tools for Hadoop Big Data Access

The channel is continuing to bring the power of Hadoop, the open source platform for Big Data, up to speed with the database and storage tools necessary to leverage that power. This week, Concurrent in unveiling two major software releases with important implications for Big Data analytics and application programming. Concurrent’s professed goal is to build “the most advanced software platform for Enterprise Big Data applications.” Its most recent new software platform, called Cascading Lingual and introduced Nov. 19, works toward that end by simplifying the interface between Hadoop data and the applications, such as business intelligence (BI) tools, that rely on that data. Concurrent is billing Cascading Lingual as “Hadoop for Everyone Else,” and says the platform:

enables virtually anyone familiar with SQL to instantly work with data stored on Hadoop using their JDBC compliant BI or desktop tool of choice. Enterprises benefit as they can execute on Big Data strategies using existing in-house resources, skills sets and product investments. Cascading Lingual drives improved enterprise productivity, time-to-market benefits and the deployment of a sane and maintainable Big Data strategy.

Also on Nov. 19, Concurrent unveiled version 2.5 of its Cascading platform, an application framework for building Java programs that leverage Hadoop. In addition to performance improvements, the update brings support for Hadoop 2—and with it YARN, a major innovation in Hadoop that represents a complete rewrite of the resource manager, formerly known as MapReduce. Cascading 2.5 also strengthens Concurrent’s channel presence by making the platform more compatible with the Hadoop tools offered by other vendors, including Cloudera, Hortonworks, MapR, Intel (INTC), Altiscale,Qubole and Amazon (AMZN) Elastic Map Reduce, the company said. Viewed broadly, Concurrent’s recent innovations, including similar advances in next-generation storage technology, reflect the drive to make Hadoop more usable. In some senses, it’s surprising that this remains an ongoing effort, since Hadoop has been around now for some time. But with Hadoop 2 out as of October, the channel has a new imperative to build solutions in this space. Stay tuned.