Concurrent Announces Availability of Cascading Lingual 

Concurrent, Inc. today announced the immediate availability of Cascading Lingual, an open source project that provides ANSI compatible SQL enabling fast and simple Big Data application development on Apache Hadoop. With Cascading Lingual, enterprises that have invested millions of dollars in business intelligence (BI) tools, such as Pentaho, Jaspersoft and Cognos, and training can now access their data on Hadoop in a matter of hours, rather than weeks. By leveraging the power and broad platform support of the Cascading application framework, Cascading Lingual lowers the barrier to enterprise application development on Hadoop.

Enterprises are rapidly adopting Hadoop to deal with growing volumes of both unstructured and semi-structured data. The need for Hadoop to easily integrate with existing data management systems, however, creates a real barrier to unlocking the full potential of Big Data and Hadoop. Cascading Lingual allows users to utilize existing SQL skills and systems to instantly create and run applications on Hadoop. As a result, data analysts, scientists and developers can now easily work with data stored on Hadoop using their favorite BI tool.

Cascading Lingual 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.

Offering a true ANSI-standard SQL interface, Cascading Lingual is compatible with all major Hadoop distributions whether on-premise or in the cloud. This project has coverage of more than 7,000 SQL-99 statements derived from sophisticated industry standard OLAP tools, delivering the broadest SQL coverage for any tool in the Hadoop ecosystem. It's innovative by making Hadoop simple and accessible, and by providing easy systems integration for multiple data stores into Hadoop by using just one SQL statement. Cascading Lingual use-case examples include:

• Data analysts, scientists and developers can now simply 'cut and paste' existing ANSI SQL code to instantly access data locked on or migrate applications to a Hadoop cluster.
• Developers can use a standard Java JDBC interface to create new Hadoop applications, or use the Cascading APIs to build applications with a mix of SQL and custom Java, Scala or Clojure code.
• Being ANSI-standard compliant and supporting the standard Java JDBC interface, companies can now query and export data from Hadoop directly into traditional BI tools.

Concurrent also announced today the release of Cascading 2.5, an open source Big Data application framework with full support and compatibility for Hadoop 2, including YARN. As enterprises upgrade to Hadoop 2 or move from one platform to another, Cascading eliminates the complexity associated with platform migration by acting as the abstraction layer between hardware platforms and applications.