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Violin Memory Announces Deduplication and Compression, Concerto 2200 Data Reduction Solution

August 2014 by Marc Jacob

Violin Memory®, Inc. announced immediate worldwide availability of its data deduplication and compression capabilities on the Concerto™ 2200 solution. This announcement extends the Company’s industry-leading set of enterprise data services for all-flash array solutions with significant data reduction capabilities.

Inline deduplication and compression on the Concerto 2200 solution gives customers maximum storage efficiency, with deduplication rates commonly between 6:1 and 10:1. Delivering up to 672 TB of usable storage at a data reduction rate of 6:1, the Concerto 2200 solution is focused on mixed and multiple workload environments and gives customers granular control at the file, share, and share group level.

The Concerto 2200 solution delivers granular inline deduplication and compression with NFS ingest capabilities and is initially targeted at Virtual Desktop (VDI) and Virtual Server (VSI) infrastructure.

The Concerto 2200 dashboard provides critical information on data reduction rates so that customers can see the effective rate of deduplication on their workload and use that information to remove the shares from deduplication, or add additional similar workloads that will benefit from data reduction.

The Concerto 2200 solution consists of two high availability (HA) appliances that deduplicate and compress shares, share groups or files from NFS and write the data to LUNs on either a Violin 6000 or 7000 series All Flash Array. The LUNs being serviced can all be on one array, or scaled across up to four arrays, depending on customer requirements. With 6:1 data reduction, the Concerto 2200 solution is capable of storing 672 TB of data or enough data for 2,500 persistent desktops in a VDI deployment at a street cost of approximately $1.81/GB or $75/desktop.

Violin data reduction services for NFS environments on the Concerto 2200 solution are available now. Deduplication and compression for block storage are expected to follow in early 2015.


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