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  • MemcacheDB, Tokyo Tyrant, Redis performance test

    I had tested the following key-value store for set() and get()

    1. Test environment

    1.1 Hardware/OS

    2 Linux boxes in a LAN, 1 server and 1 test client
    Linux Centos 5.2 64bit
    Intel(R) Xeon(R) CPU E5410  @ 2.33GHz (L2 cache: 6M), Quad-Core * 2
    8G memory
    SCSI disk (standalone disk, no other access)

    1.2 Software version

    db-4.7.25.tar.gz
    libevent-1.4.11-stable.tar.gz
    memcached-1.2.8.tar.gz
    memcachedb-1.2.1-beta.tar.gz
    redis-0.900_2.tar.gz
    tokyocabinet-1.4.9.tar.gz
    tokyotyrant-1.1.9.tar.gz

    1.3 Configuration

    Memcachedb startup parameter
    Test 100 bytes
    ./memcachedb -H /data5/kvtest/bdb/data -d -p 11212 -m 2048 -N -L 8192
    (Update: As mentioned by Steve, the 100-byte-test missed the -N paramter, so I added it and updated the data)
    Test 20k bytes
    ./memcachedb -H /data5/kvtest/mcdb/data -d -p 11212 -b 21000 -N -m 2048

    Tokyo Tyrant (Tokyo Cabinet) configuration
    Use default Tokyo Tyrant sbin/ttservctl
    use .tch database, hashtable database

    ulimsiz=”256m”
    sid=1
    dbname=”$basedir/casket.tch#bnum=50000000″ # default 1M is not enough!
    maxcon=”65536″
    retval=0

    Redis configuration
    timeout 300
    save 900 1
    save 300 10
    save 60 10000
    # no maxmemory settings

    1.4 Test client

    Client in Java, JDK1.6.0, 16 threads
    Use Memcached client java_memcached-release_2.0.1.jar
    JRedis client for Redis test, another JDBC-Redis has poor performance.

    2. Small data size test result

    Test 1, 1-5,000,000 as key, 100 bytes string value, do set, then get test, all get test has result.
    Request per second(mean)key-value-performance-1(Update)

    Store Write Read
    Memcached 55,989 50,974
    Memcachedb 25,583 35,260
    Tokyo Tyrant 42,988 46,238
    Redis 85,765 71,708

    Server Load Average

    Store Write Read
    Memcached 1.80, 1.53, 0.87 1.17, 1.16, 0.83
    MemcacheDB 1.44, 0.93, 0.64 4.35, 1.94, 1.05
    Tokyo Tyrant 3.70, 1.71, 1.14 2.98, 1.81, 1.26
    Redis 1.06, 0.32, 0.18 1.56, 1.00, 0.54

    3. Larger data size test result

    Test 2, 1-500,000 as key, 20k bytes string value, do set, then get test, all get test has result.
    Request per second(mean)
    (Aug 13 Update: fixed a bug on get() that read non-exist key)
    key-value-performance-2(update)

    Store Write Read
    Memcachedb 357 327
    Tokyo Tyrant 3,501 257
    Redis 1,542 957

    4. Some notes about the test

    When test Redis server, the memory goes up steadily, consumed all 8G and then use swap(and write speed slow down), after all memory and swap space is used, the client will get exceptions. So use Redis in a productive environment should limit to a small data size. It is another cache solution rather than a persistent storage. So compare Redis together with MemcacheDB/TC may not fair because Redis actually does not save data to disk during the test.

    Tokyo cabinet and memcachedb are very stable during heavy load, use very little memory in set test and less than physical memory in get test.

    MemcacheDB peformance is poor for write large data size(20k).

    The call response time was not monitored in this test.

    如想及时阅读Tim Yang的文章,可通过页面右上方扫码订阅最新更新。

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    242 Comments  »

    1. Traschelle

      What is the difference between Memcache and Redis? deck painting services

    2. Kate Sharma

      The provided text appears to be a configuration and test result report for various caching solutions, including Memcached, Memcachedb, Tokyo Tyrant (Tokyo Cabinet), and Redis. expertise

    3. Comparing Redis with MemcacheDB and Tokyo Cabinet may not be entirely fair, as Redis does not save data to disk during the test, unlike the other solutions mentioned. However, it is worth noting that Tokyo Cabinet and MemcacheDB demonstrate stability and consume very little memory in both set and get tests. MemcacheDB, however, performs poorly when dealing with large data sizes (20k).

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    6. Madel Smith

      It’s worth mentioning that the post did not monitor the call response time during the test, focusing primarily on the request per second performance.

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    8. Ken

      That’s interesting. I’m curious to know what your results were. Did you notice any significant differences in performance between the three?

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    9. Peter

      Wow.

    10. Are the scripts still working?

    11. Are you positive that these things are working?

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