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VMware Rolls Out vSphere Scale-Out Edition for Big Data and HPC Workloads

Today VMware introduced vSphere Scale-Out Edition for Big Data and HPC Workloads, a new solution in the vSphere product line aimed at Big Data and HPC workloads. VMware vSphere Scale-Out edition includes the features and functions most useful to Big Data and HPC workloads such as those provided by the core vSphere hypervisor and the vSphere Distributed Switch.

This new solution also enables the ability to rapidly change and provision compute nodes. The solution will be offered at an attractive price point, optimized for Big Data and HPC environments.

By virtualizing these workloads with vSphere Scale-Out, customers can benefit from:

  • Dramatic Resource Optimization — Memory and CPU utilization optimization in a virtualized environment can increase performance significantly over a physical system. VMware tests of Big Data workloads have shown that virtualized Spark cluster performance can exceed physical cluster performance by up to 10 percent.
  • Simplified Compute Node Creation — Adding more capacity to a Big Data cluster can be done by cloning VMs and giving them an identity. Clusters can be scaled up and down as needed.
  • Network Flexibility — Widely distributed systems, like most Big Data clusters, require the management of many nodes using a common central point of control across the network, which vSphere delivers through the Distributed Switch.

The new vSphere edition follows on the heels of the release of vSphere 6.5 Update 1 in July 2017. The update featured an enhanced HTML 5-based vSphere Client that now supports 90 percent of general workflows administrators rely on.

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