I have done simple performance test on my local machine, this is python script:

import redis
import sqlite3
import time

data = {}
N = 100000

for i in xrange(N):
    key = "key-"+str(i)
    value = "value-"+str(i)
    data[key] = value

r = redis.Redis("localhost", db=1)
s = sqlite3.connect("testDB")
cs = s.cursor()

try:
    cs.execute("CREATE TABLE testTable(key VARCHAR(256), value TEXT)")
except Exception as excp:
    print str(excp)
    cs.execute("DROP TABLE testTable")
    cs.execute("CREATE TABLE testTable(key VARCHAR(256), value TEXT)")

print "[---Testing SQLITE---]"
sts = time.time()
for key in data:
    cs.execute("INSERT INTO testTable VALUES(?,?)", (key, data[key]))
    #s.commit()
s.commit()
ste = time.time()
print "[Total time of sql: %s]"%str(ste-sts)

print "[---Testing REDIS---]"
rts = time.time()
r.flushdb()# for empty db
for key in data:
    r.set(key, data[key])
rte = time.time()
print "[Total time of redis: %s]"%str(rte-rts)

I expected redis to perform faster, but the result shows that it much more slower:

[---Testing SQLITE---]
[Total time of sql: 0.615846157074]
[---Testing REDIS---]
[Total time of redis: 10.9668009281]

So, the redis is memory based, what about sqlite? Why redis is so slow? When I need to use redis and when I need to use sqlite?

from the redis documentation

Redis is a server: all commands involve network or IPC roundtrips. It is meaningless to compare it to embedded data stores such as SQLite, Berkeley DB, Tokyo/Kyoto Cabinet, etc ... because the cost of most operations is precisely dominated by network/protocol management.

Which does make sense though it's an acknowledgement of speed issues in certain cases. Redis might perform a lot better than sqlite under multiples of parallel access for instance.

The right tool for the right job, sometimes it'll be redis other times sqlite other times something totally different. If this speed test is a proper showing of what your app will realistically do then sqlite will serve you better and it's good that you did this benchmark.