# DiskCache Cache Benchmarks¶

Accurately measuring performance is a difficult task. The benchmarks on this page are synthetic in the sense that they were designed to stress getting, setting, and deleting items repeatedly. Measurements in production systems are much harder to reproduce reliably. So take the following data with a grain of salt. A stated feature of DiskCache is performance so we would be remiss not to produce this page with comparisons.

The source for all benchmarks can be found under the “tests” directory in the source code repository. Measurements are reported by percentile: median, 90th percentile, 99th percentile, and maximum along with total time and miss rate. The average is not reported as its less useful in response-time scenarios. Each process in the benchmark executes 100,000 operations with ten times as many sets as deletes and ten times as many gets as sets.

Each comparison includes Memcached and Redis with default client and server settings. Note that these backends work differently as they communicate over the localhost network. The also require a server process running and maintained. All keys and values are short byte strings to reduce the network impact.

## Single Access¶

The single access workload starts one worker processes which performs all operations. No concurrent cache access occurs.

### Get¶

Above displays cache access latency at three percentiles. Notice the performance of DiskCache is faster than highly optimized memory-backed server solutions.

### Set¶

Above displays cache store latency at three percentiles. The cost of writing to disk is higher but still sub-millisecond. All data in DiskCache is persistent.

### Delete¶

Above displays cache delete latency at three percentiles. As above, deletes require disk writes but latency is still sub-millisecond.

### Timing Data¶

Not all data is easily displayed in the graphs above. Miss rate, maximum latency and total latency is recorded below.

Timings for diskcache.Cache

Action

Count

Miss

Median

P90

P99

Max

Total

get

88966

9705

12.159us

17.166us

28.849us

174.999us

1.206s

set

9021

0

68.903us

93.937us

188.112us

10.297ms

875.907ms

delete

1012

104

47.207us

66.042us

128.031us

7.160ms

89.599ms

Total

98999

2.171s

The generated workload includes a ~1% cache miss rate. All items were stored with no expiry. The miss rate is due entirely to gets after deletes.

Timings for diskcache.FanoutCache(shards=4, timeout=1.0)

Action

Count

Miss

Median

P90

P99

Max

Total

get

88966

9705

15.020us

20.027us

33.855us

437.021us

1.425s

set

9021

0

71.049us

100.136us

203.133us

9.186ms

892.262ms

delete

1012

104

48.161us

69.141us

129.952us

5.216ms

87.294ms

Total

98999

2.405s

The high maximum store latency is likely an artifact of disk/OS interactions.

Timings for diskcache.FanoutCache(shards=8, timeout=0.010)

Action

Count

Miss

Median

P90

P99

Max

Total

get

88966

9705

15.020us

20.027us

34.094us

627.995us

1.420s

set

9021

0

72.956us

100.851us

203.133us

9.623ms

927.824ms

delete

1012

104

50.783us

72.002us

132.084us

8.396ms

78.898ms

Total

98999

2.426s

Notice the low overhead of the FanoutCache. Increasing the number of shards from four to eight has a negligible impact on performance.

Timings for pylibmc.Client

Action

Count

Miss

Median

P90

P99

Max

Total

get

88966

9705

25.988us

29.802us

41.008us

139.952us

2.388s

set

9021

0

27.895us

30.994us

40.054us

97.990us

254.248ms

delete

1012

104

25.988us

29.087us

38.147us

89.169us

27.159ms

Total

98999

2.669s

Memcached performance is low latency and stable.

Timings for redis.StrictRedis

Action

Count

Miss

Median

P90

P99

Max

Total

get

88966

9705

44.107us

54.121us

73.910us

204.086us

4.125s

set

9021

0

45.061us

56.028us

75.102us

237.942us

427.197ms

delete

1012

104

44.107us

54.836us

72.002us

126.839us

46.771ms

Total

98999

4.599s

Redis performance is roughly half that of Memcached. DiskCache performs better than Redis for get operations through the Max percentile.

## Concurrent Access¶

The concurrent access workload starts eight worker processes each with different and interleaved operations. None of these benchmarks saturated all the processors.

### Get¶

Under heavy load, DiskCache gets are low latency. At the 90th percentile, they are less than half the latency of Memcached.

### Set¶

Stores are much slower under load and benefit greatly from sharding. Not displayed are latencies in excess of five milliseconds. With one shard allocated per worker, latency is within a magnitude of memory-backed server solutions.

### Delete¶

Again deletes require writes to disk. Only the FanoutCache performs well with one shard allocated per worker.

### Timing Data¶

Not all data is easily displayed in the graphs above. Miss rate, maximum latency and total latency is recorded below.

Timings for diskcache.Cache

Action

Count

Miss

Median

P90

P99

Max

Total

get

712546

71214

15.974us

23.127us

40.054us

4.953ms

12.349s

set

71530

0

94.891us

1.328ms

21.307ms

1.846s

131.728s

delete

7916

807

65.088us

1.278ms

19.610ms

1.244s

13.811s

Total

791992

157.888s

Notice the unacceptably high maximum store and delete latency. Without sharding, cache writers block each other. By default Cache objects raise a timeout error after sixty seconds.

Timings for diskcache.FanoutCache(shards=4, timeout=1.0)

Action

Count

Miss

Median

P90

P99

Max

Total

get

712546

71623

19.073us

35.048us

59.843us

12.980ms

16.849s

set

71530

0

108.004us

1.313ms

9.176ms

333.361ms

50.821s

delete

7916

767

73.195us

1.264ms

9.033ms

108.232ms

4.964s

Total

791992

72.634s

Here FanoutCache uses four shards to distribute writes. That reduces the maximum latency by a factor of ten. Note the miss rate is variable due to the interleaved operations of concurrent workers.

Timings for diskcache.FanoutCache(shards=8, timeout=0.010)

Action

Count

Miss

Median

P90

P99

Max

Total

get

712546

71106

25.034us

47.922us

101.089us

9.015ms

22.336s

set

71530

39

134.945us

1.324ms

5.763ms

16.027ms

33.347s

delete

7916

775

88.930us

1.267ms

5.017ms

13.732ms

3.308s

Total

791992

58.991s

With one shard allocated per worker and a low timeout, the maximum latency is more reasonable and corresponds to the specified 10 millisecond timeout. Some set and delete operations were therefore canceled and recorded as cache misses. The miss rate due to timeout is about 0.01% so our success rate is four-nines or 99.99%.

Timings for pylibmc.Client

Action

Count

Miss

Median

P90

P99

Max

Total

get

712546

72043

83.923us

107.050us

123.978us

617.027us

61.824s

set

71530

0

84.877us

108.004us

124.931us

312.090us

6.283s

delete

7916

796

82.970us

105.858us

123.024us

288.963us

680.970ms

Total

791992

68.788s

Memcached performance is low latency and stable even under heavy load. Notice that cache gets are three times slower in total as compared with FanoutCache. The superior performance of get operations put the overall performance of DiskCache ahead of Memcached.

Timings for redis.StrictRedis

Action

Count

Miss

Median

P90

P99

Max

Total

get

712546

72093

138.044us

169.039us

212.908us

151.121ms

101.197s

set

71530

0

138.998us

169.992us

216.007us

1.200ms

10.173s

delete

7916

752

136.137us

167.847us

211.954us

1.059ms

1.106s

Total

791992

112.476s

Redis performance is roughly half that of Memcached. Beware the impact of persistence settings on your Redis performance. Depending on your use of logging and snapshotting, maximum latency may increase significantly.