Over the past few months we have been working on SQL Server 2014 on Virtual SAN and I just wanted to peep my head out and give our customers and partners an update.
First of all, if you aren’t running SQL Server on Virtual SAN yet then let me give you 3 reasons why you might want consider it. #1, 50% Lower TCO overall by deploying SQL Server on inexpensive industry-standard server components to remove large, upfront investments. Further improve TCO with storage efficiency features like deduplication and enhanced automation capabilities. #2, Virtual SAN delivers enterprise availability for the most demanding business critical applications, capable of delivering 99.999% uptime and beyond with built-in and tunable failure tolerance settings. #3, Virtual SAN provides the simplicity of managing storage along with compute and networking in a single, tightly integrated interface--the vSphere Web Client.
In Virtual SAN 6.2 we introduced key space efficiency features such as Deduplication, Compression, and Erasure Coding (RAID5/6). During our testing one of our goals was to drive OLTP workload and test performance with the new space savings enabled. Using a four node All Flash cluster with (4) SQL Servers 2 database sizes were used; (2) 200GB and (2) 500GB. To drive the workload we used Benchmark Factory’s TPC-E. During our tests, four virtual machines on a four node All-Flash SAN cluster can consistently achieve the aggregate TPS (transactions per second) up-to 8079 (deduplication/compression enabled Virtual SAN), and can achieve predictable virtual disk latency ranging from 1ms to 2ms for read and write on average. That means with all of the space efficiency features of Virtual SAN 6.2 enabled VSAN provides great performance with minimal impact.
Looking specifically at space savings within a SQL Server environment in the chart below starting with a baseline of 5TB of data and by enabling Deduplication and compression the data size was reduced to 2.2TB which is a space savings of 56%. Then we enabled Erasure Encoding (RAID5) this reduced the data to 1.9TB and we observed a savings of up-to 62%.
