Excelero’s NVMesh® Named 2017 Product of the Year in Software-Defined Storage by Storage Magazine and SearchStorage
Gold medal winner for enabling teams to build scale-out storage like the Tech Giants, using standard servers and software for shared NVMe at local performance
SAN JOSE, CA February 13, 2018 – Excelero, a disruptor in software-defined block storage, said that its NVMesh® 1.1 server SAN was named as the Software-Defined Storage Product of the Year by the 2017 Products of the Year awards from Storage Magazine and SearchStorage. In winning the Gold medal in the software-defined storage category, NVMesh topped 10 other solutions selected as finalists and was cited the judges as a “great way for an organization to easily exploit NVMe.” Judges ranked NVMesh as #1 for innovation and #2 for value.
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One judge cited Excelero’s patented Remote Direct Drive Access (RDDA) functionality as a key performance differentiator compared with products from other vendors of rack-scale flash technology. RDDA is designed to disaggregate storage from application servers and preserve CPU for applications.
In its 16th year, the 2017 Products of the Year program evaluates innovation, performance, ease of integration into existing environments, ease of use/manageability, functionality, and value. Judges selected 14 Products of the Year in 2017 across five categories, from 47 finalists and 108 entries.
Excelero enables enterprises and service providers to design scale-out storage infrastructures leveraging standard servers and high-performance flash storage. Founded in 2014 by a team of storage veterans and inspired by the tech giants’ shared-nothing architectures for web-scale applications, the company has designed a software-defined block storage solution that meets performance and scalability requirements of the largest web-scale and enterprise applications.
With Excelero’s NVMesh, customers can build distributed, high-performance server SAN for mixed application workloads. Customers benefit from the performance of local flash, with the convenience of centralized storage while avoiding proprietary hardware lock-in and reducing the overall storage TCO. The solution has been deployed for hyper-scale Industrial IoT services, machine learning applications and massive-scale simulation visualization.
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