Please don't read too much into this. This is not a benchmark! This is a load test on a particular use case. If I were to use both for an ecommerce app, how would I do it? How fast is it?

redis_vs_mysql.txt

---------------------------------------------------------------------------------------------------
Summary
---------------------------------------------------------------------------------------------------
(PL = pipelined redis operation)

Loading one million random names (full names) like John Smith, Patty Gerbee Sr)
MySQL:                   06:05
Redis:                   02:45
Redis C ext              01:32
Redis pipelined:         00:56
Redis pipelined C ext:   00:19
Ruby just loading array: 387ms


Loading 10k ecommerce-style data (orders, users, products)
MySQL:    00:09.40
Redis:    00:14.50
Redis PL: 00:02.72
---------------------------------------------------------------------------------------------------


1,000,000 names
MethodProfiler results for: MySQLLoader.load_names
+-------------------+---------------+---------------+---------------+---------------+-------------+
| Method            | Min Time      | Max Time      | Average Time  | Total Time    | Total Calls |
+-------------------+---------------+---------------+---------------+---------------+-------------+
| #load_names       | 361309.498 ms | 361309.498 ms | 361309.498 ms | 361309.498 ms | 1           |
| #delete_all_names | 4523.151 ms   | 4523.151 ms   | 4523.151 ms   | 4523.151 ms   | 1           |
| #initialize       | 10.012 ms     | 10.012 ms     | 10.012 ms     | 10.012 ms     | 1           |
+-------------------+---------------+---------------+---------------+---------------+-------------+
6 minutes 05 seconds total (add up all total times)


10,000 users, 1,000 products, 10,000 x 3 random purchases max
MethodProfiler results for: MySQLLoader.load_sales
+-------------------+-------------+-------------+--------------+-------------+-------------+
| Method            | Min Time    | Max Time    | Average Time | Total Time  | Total Calls |
+-------------------+-------------+-------------+--------------+-------------+-------------+
| #load_orders      | 5188.282 ms | 5188.282 ms | 5188.282 ms  | 5188.282 ms | 1           |
| #load_users       | 3739.058 ms | 3739.058 ms | 3739.058 ms  | 3739.058 ms | 1           |
| #load_products    | 357.639 ms  | 357.639 ms  | 357.639 ms   | 357.639 ms  | 1           |
| #delete_all_sales | 125.877 ms  | 125.877 ms  | 125.877 ms   | 125.877 ms  | 1           |
+-------------------+-------------+-------------+--------------+-------------+-------------+
9.4 seconds


1,000,000 names
MethodProfiler results for: RedisLoader
+-------------------+---------------+---------------+---------------+---------------+-------------+
| Method            | Min Time      | Max Time      | Average Time  | Total Time    | Total Calls |
+-------------------+---------------+---------------+---------------+---------------+-------------+
| #load_names       | 165101.731 ms | 165101.731 ms | 165101.731 ms | 165101.731 ms | 1           |
| #delete_all_names | 528.833 ms    | 528.833 ms    | 528.833 ms    | 528.833 ms    | 1           |
| #initialize       | 0.068 ms      | 0.068 ms      | 0.068 ms      | 0.068 ms      | 1           |
+-------------------+---------------+---------------+---------------+---------------+-------------+
2 minutes 45 seconds


10,000 users, 1,000 products, 10,000 x 3 random purchases max
MethodProfiler results for: RedisLoader
+-------------------+--------------+--------------+--------------+--------------+-------------+
| Method            | Min Time     | Max Time     | Average Time | Total Time   | Total Calls |
+-------------------+--------------+--------------+--------------+--------------+-------------+
| #load_orders      | 10211.381 ms | 10211.381 ms | 10211.381 ms | 10211.381 ms | 1           |
| #load_users       | 3361.114 ms  | 3361.114 ms  | 3361.114 ms  | 3361.114 ms  | 1           |
| #delete_all_sales | 643.716 ms   | 643.716 ms   | 643.716 ms   | 643.716 ms   | 1           |
| #load_products    | 315.040 ms   | 315.040 ms   | 315.040 ms   | 315.040 ms   | 1           |
| #initialize       | 0.073 ms     | 0.073 ms     | 0.073 ms     | 0.073 ms     | 1           |
+-------------------+--------------+--------------+--------------+--------------+-------------+
14.5 seconds


--------------------+--------------+--------------+--------------+--------------+--------------
PIPELINED REDIS
(reduces network i/o, but sometimes you won't be able to pipeline, maybe you can't pre-queue)
--------------------+--------------+--------------+--------------+--------------+--------------

One Million Names into a List
+-------------------+--------------+--------------+--------------+--------------+-------------+
| Method            | Min Time     | Max Time     | Average Time | Total Time   | Total Calls |
+-------------------+--------------+--------------+--------------+--------------+-------------+
| #load_names       | 55011.216 ms | 55011.216 ms | 55011.216 ms | 55011.216 ms | 1           |
| #delete_all_names | 526.902 ms   | 526.902 ms   | 526.902 ms   | 526.902 ms   | 1           |
| #initialize       | 0.065 ms     | 0.065 ms     | 0.065 ms     | 0.065 ms     | 1           |
+-------------------+--------------+--------------+--------------+--------------+-------------+

Products push with made up ID (had to be ruby generated for it to work with pipeline)
+-------------------+-------------+-------------+--------------+-------------+-------------+
| Method            | Min Time    | Max Time    | Average Time | Total Time  | Total Calls |
+-------------------+-------------+-------------+--------------+-------------+-------------+
| #load_orders      | 1557.347 ms | 1557.347 ms | 1557.347 ms  | 1557.347 ms | 1           |
| #load_users       | 716.847 ms  | 716.847 ms  | 716.847 ms   | 716.847 ms  | 1           |
| #delete_all_sales | 396.674 ms  | 396.674 ms  | 396.674 ms   | 396.674 ms  | 1           |
| #load_products    | 56.369 ms   | 56.369 ms   | 56.369 ms    | 56.369 ms   | 1           |
| #initialize       | 0.080 ms    | 0.080 ms    | 0.080 ms     | 0.080 ms    | 1           |
+-------------------+-------------+-------------+--------------+-------------+-------------+
2.72 seconds

For example the join table looked like this:
Orders Table
id  | product_id | user_id
1   |    36      |   24
2   |    42      |   24

The id column is not really important in a join table.  In this case, it was
generated using .each_with_index.


Using the hiredis gem (C extension, not portable to JRuby) with pipelined
One Million Names again.
+-------------+--------------+--------------+--------------+--------------+-------------+
| Method      | Min Time     | Max Time     | Average Time | Total Time   | Total Calls |
+-------------+--------------+--------------+--------------+--------------+-------------+
| #load_names | 19209.266 ms | 19209.266 ms | 19209.266 ms | 19209.266 ms | 1           |
| #initialize | 8.809 ms     | 8.809 ms     | 8.809 ms     | 8.809 ms     | 1           |
+-------------+--------------+--------------+--------------+--------------+-------------+