Seguridad Mania.com - España y América Latina

SAN FRANCISCO, CA -- (Marketwired) -- 11/19/13 -- Concurrent, Inc., the enterprise Big Data application platform company, today introduces Cascading 2.5, an open source Big Data application framework for building robust, enterprise Big Data applications on Apache Hadoop™. The most widely used and deployed Big Data application platform now delivers support for Hadoop 2, including YARN, representing another powerful step toward delivering on the full promise of the business of data.

Enterprises today are rapidly adopting Hadoop and other computation engines to process, manage and make sense of growing volumes of both unstructured and semi-structured data. At the same time, the need to rapidly and reliably build enterprise-class applications without deep knowledge of these technologies is the greatest it has ever been. Cascading fulfills this critical need by allowing businesses to leverage their existing skillsets, investments and systems to build enterprise-class applications on Hadoop, thereby lowering the barrier to adoption. With the family of Cascading applications, enterprises can apply Java, legacy SQL and predictive modeling investments, and combine the respective outputs of multiple departments into a single data processing application.

New Cascading 2.5 features and benefits include:

• Support for Hadoop 2 and its new features, including YARN. Cascading users looking to upgrade to Hadoop 2 will now be able to seamlessly migrate their applications and take advantage of new advance features like YARN. Furthermore, Big Data applications using domain specific languages (DSLs), such as the widely used Scalding (Scala on Cascading), Cascalog (Clojure on Cascading) and PyCascading (Jython on Cascading) languages, will also seamlessly migrate to Hadoop 2.
  
  
• Added performance improvements for complex join operations and optimizations to dynamically partition and store processed data more efficiently on HDFS.
  
  
• Additional broad compatibility with other Hadoop vendors and Hadoop as a service providers, including Cloudera, Hortonworks, MapR, Intel, Altiscale, Qubole and Amazon EMR, among others give Cascading users a richer set of deployment options and services available to them, whether on-premise or in the cloud.
  
  

Concurrent also announced today the general availability of Cascading Lingual, an open source project that provides a comprehensive ANSI SQL interface. The solution allows enterprises to quickly migrate legacy SQL workloads from data warehouses and mainframes to Hadoop by simply cutting and pasting their SQL and redeploying them on Hadoop -- enabling a fast, simple and reliable way to add workloads onto Hadoop. Moreover, Cascading Lingual provides out-of-the-box support for JDBC. Enterprises that have invested millions of dollars in business intelligence (BI) tools, such as Pentaho, Jaspersoft and Cognos, and training can now also access their data on Hadoop through standard SQL interface.

Supporting Quotes
"The combined power of Concurrent's Cascading and Cloudera CDH, the world's most widely deployed Apache Hadoop distribution, delivers users an enterprise-grade, flexible framework and API for building and managing Big Data applications."
-Tim Stevens, Vice President, Corporate and Business Development, Cloudera

"As a leading provider of Hadoop-in-the-Cloud, Altiscale is focused on leveraging the potential of Hadoop 2. Our enterprise customers are very interested in the new capabilities in Hadoop 2, so it's critical that they are easy to consume. Our partnership with Concurrent and integration with Cascading 2.5 allows our customers to quickly build mission-critical, easy-to-maintain Hadoop applications to run on our 'Big Data Dialtone.'"
-Raymie Stata, CEO, Altiscale

"Within Hortonworks Data Platform 2.0, YARN enables enterprises to interact with all data in multiple ways simultaneously, making Hadoop a true multi-use data platform and allowing it to take its place in a modern data architecture. We are pleased to see Concurrent embrace these significant advances as they make Cascading 2.5 available."
- John Kreisa, Vice President of Strategic Marketing, Hortonworks

"Despite its rapid enterprise adoption, developing and building applications on Hadoop has proven to be difficult. With Hadoop 2, the community has addressed many concerns, paving a clearer path for enterprise users. At Concurrent, we're dedicated to forging a simpler path to mass Hadoop adoption by delivering a framework for building powerful and reliable data-oriented applications supporting data driven business models -- quickly and easily. Our support for Hadoop 2 was an easy decision, as we continue to be an integral part of the Hadoop and Big Data ecosystem, providing solutions that simplify application development and management for the enterprise."
-Chris Wensel, Founder and CTO, Concurrent, Inc.

Supporting Resources

• 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 2.5 will soon be publicly available and freely licensable under the Apache 2.0 License Agreement. To learn more about Cascading, visit http://cascading.org. 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 at http://concurrentinc.com.

Add to Digg Bookmark with del.icio.us Add to Newsvine