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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Based on the provided information, here is a summary of the key-value store test results:
Small data size test result (using 100-byte string values):
Memcached: Write – 55,989 requests per second, Read – 50,974 requests per second
Memcachedb: Write – 25,583 requests per second, Read – 35,260 requests per second
Tokyo Tyrant: Write – 42,988 requests per second, Read – 46,238 requests per second
Redis: Write – 85,765 requests per second, Read – 71,708 requests per second
Larger data size test result (using 20k-byte string values):
Memcachedb: Write – 357 requests per second, Read – 327 requests per second
Tokyo Tyrant: Write – 3,501 requests per second, Read – 257 requests per second
Redis: Write – 1,542 requests per second, Read – 957 requests per second
Some additional notes about the test:
The Redis server experienced memory usage issues, consuming all available RAM and swap space, which resulted in exceptions.
Tokyo Cabinet and Memcachedb showed stability during heavy loads and used minimal memory compared to physical memory in the get test.
MemcacheDB’s performance was poorer when writing larger data sizes (20k).
The response time was not monitored in this test.
Please note that these test results are specific to the hardware, software versions, and configurations mentioned in the provided information. Results may vary in different environments or with different setups. superiordraincleaning.com/
Each of these key-value stores has its own unique features, performance characteristics, and community support. The choice of which one to use depends on your specific requirements, such as data persistence, performance, scalability, and integration capabilities with your existing systems.
It’s recommended to thoroughly evaluate and benchmark each key-value store based on your needs to determine which one best aligns with your project’s requirements and constraints.
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