Final Words

 

Update: Since the publication of this review OWC appears to have switched controllers for the Mercury Extreme SSD. The current specs look similar to that of SandForce's SF-1200 controller, not the SF-1500 used in the earlier drives. Performance and long term reliability (in an enterprise environment) are both impacted. For more information, read this.

With half the capacity of the 100GB Vertex LE we looked at last week, OWC's 50GB Mercury Extreme shows that while there is a performance drop with SandForce's SF-1500 50GB platform it is limited strictly to small file random write speed. Even with the performance drop, the drive is no slower than Intel's X25-M G2. And in sequential write performance it's still significantly faster.

As I mentioned in my Vertex LE review, the SandForce controller used in this drive is still largely unproven. OWC does offer a 5 year warranty on the drive, so presumably you'll be covered if something should happen to it - I would just recommend backing up regularly.

As a SSD, 50GB is enough for a notebook or a boot/applications drive assuming you don't have too many large applications. With more inherent spare area than any other consumer SSD on the market, the Mercury should be a bit more resillient as it approaches its full capacity. Despite a competitive price tag, this 50GB drive is easily the most expensive small capacity SSD you can buy in its class. Not in terms of overall price, but in terms of cost per GB. Intel's 80GB X25-M will give you around 50% more usable space for roughly the same price. You do get more performance out of the 50GB OWC drive, but with only 50GB of space it's really a tradeoff. If you only run one or two I/O intensive applications, then the 50GB drive may be best suited for you. If you run more than just a couple of apps, you may be better off with the Intel X25-M.

I am still unsure about the long term reliability of these drives based on SandForce's controller. It will take several months for me to get to a comfortable point with them. If you're fine with being an early adopter here, by all means go for it. If the capacity doesn't turn you off, the performance at first glance looks quite good.

AnandTech Storage Bench
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  • Anand Lal Shimpi - Saturday, February 27, 2010 - link

    I present the inverse of average latency - IOPS :) Take 1/IOPS and you'll get average latency per IO. I figure it's easier to convey performance this way (bigger numbers mean better performance).

    Take care,
    Anand
  • ssdreviewer - Saturday, February 27, 2010 - link

    as the following posts already pointed out, that's not the case. it would be better you could present directly minimum/average/maximum latency data, rather than IOPS, which has no linear relations with latency under different QD. my applications rely more on latency than random r/w or IOPS, i.e. responsiveness is more crucial here. that being said, i would like to see more direct results from AS SSD and HDTune Pro access time tests. thanks.
  • jimhsu - Saturday, February 27, 2010 - link

    That method can't give you information on maximum IO latency (which for me is the critical one, if you're concerned with gaming, real time video streaming, multimedia creation, etc). A drive with 0.1 ms latency but that peaks at 500 ms could be subjectively worse than one with 0.2 ms latency but that peaks at 100 ms.
  • GullLars - Saturday, February 27, 2010 - link

    Actually, you need to take Queue Depth (QD) into account. This noted the formula is QD/IOPS, since IOPS = 1/([average accesstime]*[QD]) (this formula is known as Littles Law). If you test at QD=1, 1/IOPS = average accesstime, it's a special case. Since your IOPS tests are at QD 3 and IOPS is represented as bandwidth (IOPS*block size), you find average accesstime (at QD 3) in ms by the formula 3/([bandwidth in MB/s]/4(KB)) (not factoring in MB/KB means s->ms) = 12/[bandwidth in MB/s].

    From my SSD project a month back, i found average accesstime increases as QD increases, and when QD=#channels average accesstime double when QD doubles. The reason for increased accesstime up to QD=#flash channels are (primarily) in two parts.
    1. Statistical distribution says some channels will get multiple requests in queue while some go unused, therefore # of saturated channels < QD. The channels with queue will have single accesstime multiplied with queue lenght for average accesstime.
    2. Controller NCQ overhead, the controller adds latency when administrating the queue.
  • Paladin1211 - Friday, February 26, 2010 - link

    I just look at the AnandTech Storage Bench charts, the Kingston V+ performs so good, going neck and neck with Intel and Indilinx MLC in Heavy Workload. How could it be that fast, Anand?
  • Paladin1211 - Friday, February 26, 2010 - link

    Ops, I mean SLC, not MLC.

    Too good to be true...
  • Paladin1211 - Friday, February 26, 2010 - link

    In random write/read test, the V+ scores are so poor. Something is not right here.
  • Anand Lal Shimpi - Saturday, February 27, 2010 - link

    The heavy workload is nearly half sequential. It's a heavy downloading and multitasking workload, which has thus far paved the way for a few unexpected strong performers. Remember that most controller makers actually optimize for sequential performance, which this benchmark tests more than any of the other tests. I still can't quite figure out why the Toshiba controller does so well here other than that it must really be tuned for this type of a workload. I've run and re-run the test, the results are always the same.

    Take care,
    Anand
  • GullLars - Friday, February 26, 2010 - link

    Just thought I'd add a link to a couple of graphs i made of IOPS scaling as a function of Queue Depth for 1-4 x25-V in RAID 0 from ICH10R compared to x25-M 80GB and 160GB, and 2 x25-M 80GB RAID 0. These are in the same price range, and the graphs will show why i think Anands reviews don't show the whole truth when there is no test beyond QD 8.
    link: http://www.diskusjon.no/index.php?app=core&mod...">http://www.diskusjon.no/index.php?app=c...h_rel_mo...
    The tests were done by 3 users at a forum i frequent, the username is in front of the setup that was benched.

    The IOmeter config run was: 1GB testfile, 30 sec run, 2 sec ramp. Block sizes 0,5KB, 4KB, 16KB, 64KB. Queue Depths 1-128, 2^n stepping. This is a small part of a project from a month back mapping SSD and SSD RAID scaling by block size and queue depth (block sizes 0,5KB-64KB 2^n stepping, QD 1-128 2^n stepping).

    ATTO is also nice to show scaling of sequential performance by block size (and possibly queue depth).
  • cditty - Friday, February 26, 2010 - link

    Another great article. I have to give it to you, Anand. Your SSD coverage is by far the best on the net. I have learned so much from your various articles.

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