redict/doc/Benchmarks.html


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<!-- This is a (PRE) block.  Make sure it's left aligned or your toc title will be off. -->
<b>Benchmarks: Contents</b><br>&nbsp;&nbsp;<a href="#How Fast is Redis?">How Fast is Redis?</a><br>&nbsp;&nbsp;<a href="#Latency percentiles">Latency percentiles</a>
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                <h1 class="wikiname">Benchmarks</h1>

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                    <h1><a name="How Fast is Redis?">How Fast is Redis?</a></h1>Redis includes the <code name="code" class="python">redis-benchmark</code> utility that simulates <a href="SETs.html">SETs</a>/GETs done by N clients at the same time sending M total queries (it is similar to the Apache's <code name="code" class="python">ab</code> utility). Below you'll find the full output of the benchmark executed against a Linux box.<br/><br/><ul><li> The test was done with 50 simultaneous clients performing 100000 requests.</li><li> The value SET and GET is a 256 bytes string.</li><li> The Linux box is running <b>Linux 2.6</b>, it's <b>Xeon X3320 2.5Ghz</b>.</li><li> Text executed using the loopback interface (127.0.0.1).</li></ul>
Results: <b>about 110000 <a href="SETs.html">SETs</a> per second, about 81000 GETs per second.</b><h1><a name="Latency percentiles">Latency percentiles</a></h1><pre class="codeblock python" name="code">
./redis-benchmark -n 100000

====== SET ======
  100007 requests completed in 0.88 seconds
  50 parallel clients
  3 bytes payload
  keep alive: 1

58.50% &lt;= 0 milliseconds
99.17% &lt;= 1 milliseconds
99.58% &lt;= 2 milliseconds
99.85% &lt;= 3 milliseconds
99.90% &lt;= 6 milliseconds
100.00% &lt;= 9 milliseconds
114293.71 requests per second

====== GET ======
  100000 requests completed in 1.23 seconds
  50 parallel clients
  3 bytes payload
  keep alive: 1

43.12% &lt;= 0 milliseconds
96.82% &lt;= 1 milliseconds
98.62% &lt;= 2 milliseconds
100.00% &lt;= 3 milliseconds
81234.77 requests per second

====== INCR ======
  100018 requests completed in 1.46 seconds
  50 parallel clients
  3 bytes payload
  keep alive: 1

32.32% &lt;= 0 milliseconds
96.67% &lt;= 1 milliseconds
99.14% &lt;= 2 milliseconds
99.83% &lt;= 3 milliseconds
99.88% &lt;= 4 milliseconds
99.89% &lt;= 5 milliseconds
99.96% &lt;= 9 milliseconds
100.00% &lt;= 18 milliseconds
68458.59 requests per second

====== LPUSH ======
  100004 requests completed in 1.14 seconds
  50 parallel clients
  3 bytes payload
  keep alive: 1

62.27% &lt;= 0 milliseconds
99.74% &lt;= 1 milliseconds
99.85% &lt;= 2 milliseconds
99.86% &lt;= 3 milliseconds
99.89% &lt;= 5 milliseconds
99.93% &lt;= 7 milliseconds
99.96% &lt;= 9 milliseconds
100.00% &lt;= 22 milliseconds
100.00% &lt;= 208 milliseconds
88109.25 requests per second

====== LPOP ======
  100001 requests completed in 1.39 seconds
  50 parallel clients
  3 bytes payload
  keep alive: 1

54.83% &lt;= 0 milliseconds
97.34% &lt;= 1 milliseconds
99.95% &lt;= 2 milliseconds
99.96% &lt;= 3 milliseconds
99.96% &lt;= 4 milliseconds
100.00% &lt;= 9 milliseconds
100.00% &lt;= 208 milliseconds
71994.96 requests per second
</pre>Notes: changing the payload from 256 to 1024 or 4096 bytes does not change the numbers significantly (but reply packets are glued together up to 1024 bytes so GETs may be slower with big payloads). The same for the number of clients, from 50 to 256 clients I got the same numbers. With only 10 clients it starts to get a bit slower.<br/><br/>You can expect different results from different boxes. For example a low profile box like <b>Intel core duo T5500 clocked at 1.66Ghz running Linux 2.6</b> will output the following:
<pre class="codeblock python python" name="code">
 ./redis-benchmark -q -n 100000
SET: 53684.38 requests per second
GET: 45497.73 requests per second
INCR: 39370.47 requests per second
LPUSH: 34803.41 requests per second
LPOP: 37367.20 requests per second
</pre>Another one using a 64 bit box, a Xeon L5420 clocked at 2.5 Ghz:<br/><br/><pre class="codeblock python python python" name="code">
 ./redis-benchmark -q -n 100000
PING: 111731.84 requests per second
SET: 108114.59 requests per second
GET: 98717.67 requests per second
INCR: 95241.91 requests per second
LPUSH: 104712.05 requests per second
LPOP: 93722.59 requests per second
</pre>
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html doc updated 2009-11-28 14:59:06 -05:00
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			`<b>Benchmarks: Contents</b><br>  <a href="#How Fast is Redis?">How Fast is Redis?</a><br>  <a href="#Latency percentiles">Latency percentiles</a>`
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			`<h1 class="wikiname">Benchmarks</h1>`

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HTML doc update 2009-12-05 10:58:10 -05:00			<h1><a name="How Fast is Redis?">How Fast is Redis?</a></h1>Redis includes the <code name="code" class="python">redis-benchmark</code> utility that simulates <a href="SETs.html">SETs</a>/GETs done by N clients at the same time sending M total queries (it is similar to the Apache's <code name="code" class="python">ab</code> utility). Below you'll find the full output of the benchmark executed against a Linux box.<br/><br/><ul><li> The test was done with 50 simultaneous clients performing 100000 requests.</li><li> The value SET and GET is a 256 bytes string.</li><li> The Linux box is running <b>Linux 2.6</b>, it's <b>Xeon X3320 2.5Ghz</b>.</li><li> Text executed using the loopback interface (127.0.0.1).</li></ul>
			`Results: <b>about 110000 <a href="SETs.html">SETs</a> per second, about 81000 GETs per second.</b><h1><a name="Latency percentiles">Latency percentiles</a></h1><pre class="codeblock python" name="code">`
html doc updated 2009-11-28 14:59:06 -05:00			`./redis-benchmark -n 100000`

			`====== SET ======`
			`100007 requests completed in 0.88 seconds`
			`50 parallel clients`
			`3 bytes payload`
			`keep alive: 1`

			`58.50% <= 0 milliseconds`
			`99.17% <= 1 milliseconds`
			`99.58% <= 2 milliseconds`
			`99.85% <= 3 milliseconds`
			`99.90% <= 6 milliseconds`
			`100.00% <= 9 milliseconds`
			`114293.71 requests per second`

			`====== GET ======`
			`100000 requests completed in 1.23 seconds`
			`50 parallel clients`
			`3 bytes payload`
			`keep alive: 1`

			`43.12% <= 0 milliseconds`
			`96.82% <= 1 milliseconds`
			`98.62% <= 2 milliseconds`
			`100.00% <= 3 milliseconds`
			`81234.77 requests per second`

			`====== INCR ======`
			`100018 requests completed in 1.46 seconds`
			`50 parallel clients`
			`3 bytes payload`
			`keep alive: 1`

			`32.32% <= 0 milliseconds`
			`96.67% <= 1 milliseconds`
			`99.14% <= 2 milliseconds`
			`99.83% <= 3 milliseconds`
			`99.88% <= 4 milliseconds`
			`99.89% <= 5 milliseconds`
			`99.96% <= 9 milliseconds`
			`100.00% <= 18 milliseconds`
			`68458.59 requests per second`

			`====== LPUSH ======`
			`100004 requests completed in 1.14 seconds`
			`50 parallel clients`
			`3 bytes payload`
			`keep alive: 1`

			`62.27% <= 0 milliseconds`
			`99.74% <= 1 milliseconds`
			`99.85% <= 2 milliseconds`
			`99.86% <= 3 milliseconds`
			`99.89% <= 5 milliseconds`
			`99.93% <= 7 milliseconds`
			`99.96% <= 9 milliseconds`
			`100.00% <= 22 milliseconds`
			`100.00% <= 208 milliseconds`
			`88109.25 requests per second`

			`====== LPOP ======`
			`100001 requests completed in 1.39 seconds`
			`50 parallel clients`
			`3 bytes payload`
			`keep alive: 1`

			`54.83% <= 0 milliseconds`
			`97.34% <= 1 milliseconds`
			`99.95% <= 2 milliseconds`
			`99.96% <= 3 milliseconds`
			`99.96% <= 4 milliseconds`
			`100.00% <= 9 milliseconds`
			`100.00% <= 208 milliseconds`
			`71994.96 requests per second`
			</pre>Notes: changing the payload from 256 to 1024 or 4096 bytes does not change the numbers significantly (but reply packets are glued together up to 1024 bytes so GETs may be slower with big payloads). The same for the number of clients, from 50 to 256 clients I got the same numbers. With only 10 clients it starts to get a bit slower.<br/><br/>You can expect different results from different boxes. For example a low profile box like <b>Intel core duo T5500 clocked at 1.66Ghz running Linux 2.6</b> will output the following:
			`<pre class="codeblock python python" name="code">`
			`./redis-benchmark -q -n 100000`
			`SET: 53684.38 requests per second`
			`GET: 45497.73 requests per second`
			`INCR: 39370.47 requests per second`
			`LPUSH: 34803.41 requests per second`
			`LPOP: 37367.20 requests per second`
			`</pre>Another one using a 64 bit box, a Xeon L5420 clocked at 2.5 Ghz:<br/><br/><pre class="codeblock python python python" name="code">`
			`./redis-benchmark -q -n 100000`
			`PING: 111731.84 requests per second`
			`SET: 108114.59 requests per second`
			`GET: 98717.67 requests per second`
			`INCR: 95241.91 requests per second`
			`LPUSH: 104712.05 requests per second`
			`LPOP: 93722.59 requests per second`
			`</pre>`
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