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November 30, 2015
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EMC Elastic Cloud Storage now Certified on HDP

Customers who are dealing with massive growth of large unstructured data sources need to evaluate their storage architecture for scalability, flexibility and ease of management. In a recent study, performed by the Enterprise Strategy Group, IT decision makers were asked to identify their biggest storage challenges. In addition to rapid data growth rate, they also pointed to hardware costs, data protection and staffing costs. Object-based storage solutions aim at addressing a number of these challenges, and EMC’s answer comes with Elastic Cloud Storage (ECS). With ECS, customers can take benefit from a software-defined object storage system with the Hortonworks Data Platform for analytics and unlocking business insights.

Through the certification of ECS 2.2 release on HDP 2.3 we validated the integration of both platforms, thereby saving customers time to implement the solution, while providing them with an assurance of interoperability. To achieve this, EMC developed a custom Ambari stack to ease deployment of HDP on any Hadoop Compatible File System (HCFS) like ECS.

Hortonworks certification program is the most comprehensive certification for Hadoop platforms on the market and offers easing the adoption of a modern data architecture. As such, we are excited to announce that ECS 2.2 obtained 3 levels of certification:


HDP Certified: Reviewed for architectural best practices, validated for integration interoperability and consistency and, verified under varied workloads.


HDPYarnCertifiedYARN Ready: Verified to work within YARN, able to process Hadoop data in-place, without interfering with other YARN Ready tools and applications.



Ops Ready: Passed rigorous integration tests with the operational framework for Apache Hadoop and simplify the monitoring and management of the platform and for applications on HDP.



If you are interested in learning more about this, register now for a joint EMC and Hortonworks webinar “Hadoop Everywhere – Geo Distributed Storage for Big Data” on Thursday 10th December at:


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