It’s been a while since we reported on Storage Performance Council (SPC) Least Response Time (LRT) results (see Chart of the month: SPC LRT[TM]). This is one of the charts we produce for our monthly dispatch on storage performance (quarterly report on SPC results).
Since our last blog post on this subject there have been 6 new entries in LRT Top 10 (#3-6 &, 9-10). As can be seen here which combines SPC-1 and 1/E results, response times vary considerably. 7 of these top 10 LRT results come from subsystems which either have all SSDs (#1-4, 7 & 9) or have a large NAND cache (#5). The newest members on this chart were the NetApp 3270A and the Xiotech Emprise 5000-300GB disk drives which were published recently.
The NetApp FAS3270A, a mid-range subsystem with 1TB of NAND cache (512MB in each controller) seemed to do pretty well here with all SSD systems doing better than it and a pair of all SSD systems doing worse than it. Coming in under 1msec LRT is no small feat. We are certain the NAND cache helped NetApp achieve their superior responsiveness.
What the Xiotech Emprise 5000-300GB storage subsystem is doing here is another question. They have always done well on an IOPs/drive basis (see SPC-1&-1/E results IOPs/Drive – chart of the month) but being top ten in LRT had not been their forte, previously. How one coaxes a 1.47 msec LRT out of a 20 drive system that costs only ~$41K, 12X lower than the median price(~$509K) of the other subsystems here is a mystery. Of course, they were using RAID 1 but so were half of the subsystems on this chart.
It’s nice that some turnover in this top 10 LRT. I still contend that response time is an important performance metric for many storage workloads (see my IO throughput vs. response time and why it matters post) and improvement over time validates my thesis. Also I received many comments discussing the merits of database latencies for ESRP v3 (Exchange 2010) results, (see my Microsoft Exchange Perfomance ESRP v3.0 results – chart of the month post). You can judge the results of that lengthy discussion for yourselves.
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As always, we welcome any constructive suggestions on how to improve our storage performance analysis.
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