Seagate Announces Hadoop Workflow Accelerator

Seagate Technology, a provider of storage solutions, has introduced ClusterStor Hadoop Workflow AcceleratorThe solution provides a set of Hadoop optimization tools, services and support that leverages and improves the performance of the company’s ClusterStor scale-out storage system, designed for big data analysis..

The Hadoop Workflow Accelerator is expected to be a boon to computationally intensive high performance data analytics environments, enabling them to achieve a significant reduction in data transfer time. Seagate’s Hadoop Workflow Accelerator is scheduled to be available in January as a set of distinct product bundles, with varying levels of performance optimization, services and support

According to the company, the Seagate ClusterStor systems’ scale-out HPC architecture enables a central repository allowing both HPC and Hadoop analytics tools to be run simultaneously on the same data sets in ClusterStor. The Hadoop Workflow Accelerator significantly reduces time to results by enabling immediate Hadoop data processing from the start of each job, and eliminates the time consuming step of bulk copying large amounts of data from a separate data repository. With the Accelerator, Hadoop environments can now scale computing and storage resources independently, increasing flexibility to optimize analysis resources, while supporting centralized high-performance data repositories of 100’s of PBs of storage capacity.

“Organizations not only want to manage the tremendous volume of data that they are collecting from a wide variety of sources, they also want to derive new insights that enable actionable intelligence and improve operational efficiency,” said Ken Claffey, Vice President of ClusterStor, Seagate Cloud Systems and Solutions. “The Hadoop Workflow Accelerator meets our customers’ performance demands and optimizes the performance of Hadoop Ecosystem deployments, thus helping customers achieve the fastest time to results for their data intensive workloads and hardware configuration.”

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