I had tested the following key-value store for set() and get()
- MemcacheDB, use memcached client protocol.
- Tokyo Tyrant (Tokyo Cabinet), use memcached client protocol
- Redis, use JRedis Java client
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)
| 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)
| 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.
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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
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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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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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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These key-value stores were tested on a Linux environment with specific hardware, OS, and software versions. cincinnatiseo.io/
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MemcacheDB is a simple and lightweight key-value store. It is easy to set up and use, and it is very efficient for storing small amounts of data. However, it is not as scalable as some of the other key-value stores.
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Testing the performance of MemcacheDB, Tokyo Tyrant, and Redis can provide valuable insights into their capabilities and suitability for different use cases. It’s essential to benchmark these database systems to make informed decisions about which one best meets your specific requirements.
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