Available now and built for the enterprise; Cascading Lingual enables users to query and export data from Hadoop directly into any traditional BI solution

SAN FRANCISCO – Nov. 19, 2013 – Concurrent, Inc., the enterprise Big Data application platform company, 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: Hadoop for Everyone Else

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 Hadoopdistributions 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.

Cascading is the most widely used and deployed application framework for building robust, enterprise Big Data applications on Hadoop. Companies, including The Climate Corporation, eBay, Etsy, Square, Trulia, TeleNav and Twitter are using Cascading to streamline data processing, data filtering and workflow optimization for large volumes of unstructured and semi-structured data. Cascading is also at the core of popular language extensions including PyCascading (Python + Cascading), Scalding (Scala + Cascading) and Cascalog (Clojure + Cascading) – open source projects sponsored by Twitter. Cascading has become the most reliable and repeatable way of building and deploying Big Data applications.

Supporting Quotes

“Cascading is an important component to the Big Data application development ecosystem, and Lingual is another step forward in making it significantly easier to build Big Data apps. Now, Amazon Elastic MapReduce (EMR) customers can leverage Lingual to integrate disparate data stores on Amazon Web Services (AWS) with services such as Amazon S3 and Amazon Redshift, and they can process the data and store it in Amazon EMR through one standard ANSI SQL statement. This makes it easier for customers to query data with their favorite BI tool.”
-Steve McPherson, Group Manager, Amazon EMR at AWS

“Concurrent is committed to our mission of simplifying enterprise application development and deployment on Hadoop. Cascading Lingual abstracts the complexity of Hadoop into languages and interfaces that people already know, providing a pragmatic, yet powerful, tool for enterprises that are looking to make the most of their in-house talent. With Cascading Lingual, companies can now make the most of Hadoop without the costly investment in additional BI tools and training.”
-Gary Nakamura, Chief Executive Officer, Concurrent, Inc.

Supporting Resources

Cascading Lingual website: http://cascading.org/lingual
Cascading website: http://cascading.org
Company: http://concurrentinc.com
Contact us: http://concurrentinc.com/contact
Follow us on Twitter: http://twitter.com/concurrent

Availability and Pricing

Cascading Lingual is now publicly available and freely licensable under the Apache 2.0 License Agreement. To learn more about the Cascading Lingual project, visit http://cascading.org/lingual. Concurrent also offers standard and premium support subscriptions for enterprise use. To learn more about Concurrent’s offerings, please visit http://concurrentinc.com.

About Concurrent, Inc.

Concurrent, Inc. is the enterprise Big Data application platform company. Founded in 2008, Concurrent simplifies Big Data application development, deployment and management on Apache Hadoop. We are the company behind Cascading, the most widely used and deployed technology for building Big Data applications with more than 110,000 user downloads a month. Enterprises including Twitter, eBay, The Climate Corporation, Square and Etsy all rely on Concurrent’s technology to drive their Big Data deployments.  Concurrent is headquartered in San Francisco. Visit Concurrent online athttp://concurrentinc.com.

Media Contact
Danielle Salvato-Earl
Kulesa Faul for Concurrent, Inc.
(650) 340 1982
concurrent@kulesafaul.com