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Fast storage: 8 SSD Intel X-25M 80GB benchmarks


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I appreciate opportunity Jos van Dongen from Tholis Consulting gave me. He granted me access to servers with 8 attached Intel X-25M 80GB MLC cards. The cards attached to 2 Adaptec 5805 raid controllers, with 4 cards per controller.

The cost of setup is 8 x 260$ (X-25M) + 2×500$ (Adaptec 5805) = ~3000$.
Available space varies in depends on raid setup from 300GB to 600GB.

The logical comparison is to compare results with FusionIO 320GB MLC card, so I will copy results from FusionIO 320GB MLC benchmarks.

For benchmarks I used sysbench fileio benchmark.
All raw results are available on Percona benchmarks wiki, there I will highlight most interesting points.

Couple words on tested setups. We used two configurations:

  • In first runs (software) each card connected as individual card to Adaptec, so in OS we see 8 individual cards. Card configured in software RAIDs: RAID0, RAID10, RAID5, RAID50
  • In second round (marked as hardware) each Adaptec is configured as hardware RAID0 over 4 cards, so in OS we see 2 devices. Devices connected in software RAIDs: RAID0 and RAID10 with different OS schedules over each device.

I should highlight I do not see usage in production for RAID0, as in my opinion SSD cards
are not reached enough level of reliability yet (see comments to post FusionIO 320GB MLC benchmarks), however I put results here to show theoretical maximal results.

So let’s start with random reads:

rand-read

I’d say SSDs show comparable results with FusionIO on 16+ threads, however on 4-8 threads difference is significant. On SSD you can get 160MB/sec for 4 threads and 260MB/sec for 8 threads.

Random writes:
rand-write

There couple things to note (beside SSD is doing much worse than FusionIO).
1. Something is wrong with scaling random writes in this setup. It is point for research,
I think there some serialization in Linux software raid or Linux scheduler or on Adaptec hardware level.
2. Cards connected in hardware raids show worse results than card connected as single devices (you can see results on https://www.percona.com/docs/wiki/benchmark:ssd:start, in summary table, randwr rows)
3. For cards connected in hardware raids, DEADLINE performs much worse than CFQ.

Sequential reads:
seq-read

– For sequential reads you can get pretty decent results from SSD (230MB/sec on 4+ threads)
– Cards connected in hardware raid is doing much better
– DEADLINE outperforms CFQ here (which is different from random writes)
– Software raid0 performed pretty bad, so I chosen to show hardware-raid0 results

Sequential writes:
seq-write

I’d say sequential writes is hard task for both SSDs and FusionIO, it does not scale well.
You may want to look into another options if your load requires sequential writes (e.g. like I
put InnoDB transactional logs on rotation based drives instead of SSD in my InnoDB on FusionIO benchmarks).

So in summary I can say

  • With SSD drives you can get decent results for random and sequential reads.
    I think it is competitive vs FusionIO if we look into price/performance analysis (remember FusionIO is twice as expensive)
  • Random writes did not work for me as expected, and this is point for investigations
  • RAID5, as expected, is only competitive for reads, but not writes
  • Complexity of having 8 SSD drives may be significant. You may want to
    look into different options: connect them in software or hardware raids, what scheduler to
    pick, etc. I suggest to run sysbench fileio or similar (i.e. iozone) to check if you get performance you expect
  • In my opinion maintaining 8 SSD cards per server is much more hassle than
    deal with single FusionIO card, however there is important point that with SSD you may
    “hot”remove and insert cards, while for FusionIO, which put into PCI-E bus, you need
    to shutdown server to replace it
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Vadim Tkachenko

Vadim Tkachenko co-founded Percona in 2006 and serves as its Chief Technology Officer. Vadim leads Percona Labs, which focuses on technology research and performance evaluations of Percona’s and third-party products. Percona Labs designs no-gimmick tests of hardware, filesystems, storage engines, and databases that surpass the standard performance and functionality scenario benchmarks. Vadim’s expertise in LAMP performance and multi-threaded programming help optimize MySQL and InnoDB internals to take full advantage of modern hardware. Oracle Corporation and its predecessors have incorporated Vadim’s source code patches into the mainstream MySQL and InnoDB products. He also co-authored the book High Performance MySQL: Optimization, Backups, and Replication 3rd Edition.



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Benchmarks, MySQL


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