HP Delivers Industry's First Purpose-Built Server For Big Data
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HP Delivers Industry's First Purpose-Built Server For Big Data

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Bangalore: HP unveiled the industry’s first server built to help clients operationalize Big Data, drive new business opportunities and save up to $1 million over three years.



With the advent of Big Data software and the promise that it brings, many organizations have tried to deploy these solutions on existing architectures not designed to handle the specific needs of these workloads. As a result, the outcomes from these early deployments have been suboptimal from a performance and cost perspective. 



“Big Data application environments such as Hadoop, MPP data warehouses, Big Data analytics and object stores have very different workload requirements,” said Dan Vesset, vice president, Business Analytics Research, IDC. “Given the large and varied amounts of fast-moving data that needs to be stored and accessed quickly and the different requirements of end users, these workloads can be highly varied, complex and inefficient to manage if run on traditional hardware infrastructure. In order to fully embrace the promise of Big Data, it is critical that the underlying infrastructure be optimized for the workload.”



The new HP ProLiant SL4500 server series is the only solution purpose built for Big Data environments. It provides maximum performance, productivity and cost-effectiveness in an ultradense solution required by these workloads. Built on HP Converged Infrastructure, the new server offers a highly efficient design that consumes up to 50 percent less space, 61 percent less power and 31 percent lower cost while using 63 percent fewer cables.



“Enterprises that leverage Cloudera’s Platform for Big Data to unlock insights across all of their data benefit from deploying infrastructure components optimized for the extreme demands of Big Data workloads,” said Amr Awadallah, chief technology officer, Cloudera. “By designing a server purpose built for Big Data, HP is offering the market a seamless new approach to processing large data sets efficiently and cost-effectively.”



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