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Improved benchmark, fixed bugs and SQLite parameters.

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- Based on suggestions on the sqlite-users mailing list,
  we removed the superfluous index on the primary key 
  for SQLite's benchmarks, and turned write-ahead logging 
  ("WAL") on. This led to performance improvements for SQLite.

- Based on a suggestion by Florian Weimer on the leveldb
  mailing list, we disabled hard drive write-caching via
  hdparm when testing synchronous writes. This led to
  performance losses for LevelDB and Kyoto TreeDB.

- Fixed a mistake in 2.A.->Random where the bar sizes
  were switched for Kyoto TreeDB and SQLite.



git-svn-id: https://leveldb.googlecode.com/svn/trunk@45 62dab493-f737-651d-591e-8d6aee1b9529
This commit is contained in:
gabor@google.com 2011-07-29 21:35:05 +00:00
parent b9ef9141ba
commit 1bfbe76b4e
2 changed files with 69 additions and 67 deletions
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10
doc/bench/db_bench_sqlite3.cc
View File

@ -74,7 +74,7 @@ static bool FLAGS_use_existing_db = false;
static bool FLAGS_transaction = true; static bool FLAGS_transaction = true;
// If true, we enable Write-Ahead Logging // If true, we enable Write-Ahead Logging
static bool FLAGS_WAL_enabled = false; static bool FLAGS_WAL_enabled = true;
inline inline
static void ExecErrorCheck(int status, char *err_msg) { static void ExecErrorCheck(int status, char *err_msg) {
@ -448,16 +448,20 @@ class Benchmark {
// Change journal mode to WAL if WAL enabled flag is on // Change journal mode to WAL if WAL enabled flag is on
if (FLAGS_WAL_enabled) { if (FLAGS_WAL_enabled) {
std::string WAL_stmt = "PRAGMA journal_mode = WAL"; std::string WAL_stmt = "PRAGMA journal_mode = WAL";
// LevelDB's default cache size is a combined 4 MB
std::string WAL_checkpoint = "PRAGMA wal_autocheckpoint = 4096";
status = sqlite3_exec(db_, WAL_stmt.c_str(), NULL, NULL, &err_msg); status = sqlite3_exec(db_, WAL_stmt.c_str(), NULL, NULL, &err_msg);
ExecErrorCheck(status, err_msg); ExecErrorCheck(status, err_msg);
status = sqlite3_exec(db_, WAL_checkpoint.c_str(), NULL, NULL, &err_msg);
ExecErrorCheck(status, err_msg);
} }
// Change locking mode to exclusive and create tables/index for database // Change locking mode to exclusive and create tables/index for database
std::string locking_stmt = "PRAGMA locking_mode = EXCLUSIVE"; std::string locking_stmt = "PRAGMA locking_mode = EXCLUSIVE";
std::string create_stmt = std::string create_stmt =
"CREATE TABLE test (key blob, value blob, PRIMARY KEY(key))"; "CREATE TABLE test (key blob, value blob, PRIMARY KEY(key))";
std::string index_stmt = "CREATE INDEX keyindex ON test (key)"; std::string stmt_array[] = { locking_stmt, create_stmt };
std::string stmt_array[] = { locking_stmt, create_stmt, index_stmt };
int stmt_array_length = sizeof(stmt_array) / sizeof(std::string); int stmt_array_length = sizeof(stmt_array) / sizeof(std::string);
for (int i = 0; i < stmt_array_length; i++) { for (int i = 0; i < stmt_array_length; i++) {
status = sqlite3_exec(db_, stmt_array[i].c_str(), NULL, NULL, &err_msg); status = sqlite3_exec(db_, stmt_array[i].c_str(), NULL, NULL, &err_msg);

126
doc/benchmark.html
View File

@ -85,7 +85,7 @@ div.bsql {
<p>In order to test LevelDB's performance, we benchmark it against other well-established database implementations. We compare LevelDB (revision 39) against <a href="http://www.sqlite.org/">SQLite3</a> (version 3.7.6.3) and <a href="http://fallabs.com/kyotocabinet/spex.html">Kyoto Cabinet's</a> (version 1.2.67) TreeDB (a B+Tree based key-value store). We would like to acknowledge Scott Hess and Mikio Hirabayashi for their suggestions and contributions to the SQLite3 and Kyoto Cabinet benchmarks, respectively.</p> <p>In order to test LevelDB's performance, we benchmark it against other well-established database implementations. We compare LevelDB (revision 39) against <a href="http://www.sqlite.org/">SQLite3</a> (version 3.7.6.3) and <a href="http://fallabs.com/kyotocabinet/spex.html">Kyoto Cabinet's</a> (version 1.2.67) TreeDB (a B+Tree based key-value store). We would like to acknowledge Scott Hess and Mikio Hirabayashi for their suggestions and contributions to the SQLite3 and Kyoto Cabinet benchmarks, respectively.</p>
<p>Benchmarks were all performed on a six-core Intel(R) Xeon(R) CPU X5650 @ 2.67GHz, with 12288 KB of total L3 cache and 12 GB of DDR3 RAM at 1333 MHz. (Note that LevelDB uses at most two CPUs since the benchmarks are single threaded: one to run the benchmark, and one for background compactions.) We ran the benchmarks on two machines (with identical processors), one with an Ext3 file system and one with an Ext4 file system. The machine with the Ext3 file system has a SATA Hitachi HDS721050CLA362 hard drive. The machine with the Ext4 file system has a SATA Samsung HD502HJ hard drive. Both hard drives spin at 7200 RPM. The numbers reported below are the median of three measurements.</p> <p>Benchmarks were all performed on a six-core Intel(R) Xeon(R) CPU X5650 @ 2.67GHz, with 12288 KB of total L3 cache and 12 GB of DDR3 RAM at 1333 MHz. (Note that LevelDB uses at most two CPUs since the benchmarks are single threaded: one to run the benchmark, and one for background compactions.) We ran the benchmarks on two machines (with identical processors), one with an Ext3 file system and one with an Ext4 file system. The machine with the Ext3 file system has a SATA Hitachi HDS721050CLA362 hard drive. The machine with the Ext4 file system has a SATA Samsung HD502HJ hard drive. Both hard drives spin at 7200 RPM and have hard drive write-caching enabled (using `hdparm -W 1 [device]`). The numbers reported below are the median of three measurements.</p>
<h4>Benchmark Source Code</h4> <h4>Benchmark Source Code</h4>
<p>We wrote benchmark tools for SQLite and Kyoto TreeDB based on LevelDB's <span class="code">db_bench</span>. The code for each of the benchmarks resides here:</p> <p>We wrote benchmark tools for SQLite and Kyoto TreeDB based on LevelDB's <span class="code">db_bench</span>. The code for each of the benchmarks resides here:</p>
@ -97,9 +97,9 @@ div.bsql {
<h4>Custom Build Specifications</h4> <h4>Custom Build Specifications</h4>
<ul> <ul>
<li>LevelDB: LevelDB was compiled with the <a href="http://code.google.com/p/google-perftools">tcmalloc</a> library and the <a href="http://code.google.com/p/snappy/">Snappy</a> compression library. Assertions were disabled.</li> <li>LevelDB: LevelDB was compiled with the <a href="http://code.google.com/p/google-perftools">tcmalloc</a> library and the <a href="http://code.google.com/p/snappy/">Snappy</a> compression library (revision 33). Assertions were disabled.</li>
<li>TreeDB: TreeDB was compiled using the <a href="http://www.oberhumer.com/opensource/lzo/">LZO</a> compression library. Furthermore, we enabled the TSMALL and TLINEAR options when opening the database in order to reduce the footprint of each record.</li> <li>TreeDB: TreeDB was compiled using the <a href="http://www.oberhumer.com/opensource/lzo/">LZO</a> compression library (version 2.03). Furthermore, we enabled the TSMALL and TLINEAR options when opening the database in order to reduce the footprint of each record.</li>
<li>SQLite: We tuned SQLite's performance, by setting its locking mode to exclusive. We left SQLite's <a href="http://www.sqlite.org/draft/wal.html">write-ahead logging</a> disabled since that is the default configuration. (Enabling write-ahead-logging improves SQLite's write performance by roughly 30%, but the character of the comparisons below does not change significantly.)</li> <li>SQLite: We tuned SQLite's performance, by setting its locking mode to exclusive. We also enabled SQLite's <a href="http://www.sqlite.org/draft/wal.html">write-ahead logging</a>.</li>
</ul> </ul>
<h2>1. Baseline Performance</h2> <h2>1. Baseline Performance</h2>
@ -130,8 +130,8 @@ parameters are varied. For the baseline:</p>
<td class="c2">1,010,000 ops/sec</td> <td class="c2">1,010,000 ops/sec</td>
<td class="c3"><div class="bkct" style="width:95px">&nbsp;</div></td> <td class="c3"><div class="bkct" style="width:95px">&nbsp;</div></td>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">186,000 ops/sec</td> <td class="c2">174,000 ops/sec</td>
<td class="c3"><div class="bsql" style="width:16px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:15px">&nbsp;</div></td>
</table> </table>
<h3>B. Random Reads</h3> <h3>B. Random Reads</h3>
<table class="bn bnbase"> <table class="bn bnbase">
@ -142,8 +142,8 @@ parameters are varied. For the baseline:</p>
<td class="c2">151,000 ops/sec</td> <td class="c2">151,000 ops/sec</td>
<td class="c3"><div class="bkct" style="width:350px">&nbsp;</div></td> <td class="c3"><div class="bkct" style="width:350px">&nbsp;</div></td>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">146,000 ops/sec</td> <td class="c2">134,000 ops/sec</td>
<td class="c3"><div class="bsql" style="width:337px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:310px">&nbsp;</div></td>
</table> </table>
<h3>C. Sequential Writes</h3> <h3>C. Sequential Writes</h3>
<table class="bn bnbase"> <table class="bn bnbase">
@ -154,8 +154,8 @@ parameters are varied. For the baseline:</p>
<td class="c2">342,000 ops/sec</td> <td class="c2">342,000 ops/sec</td>
<td class="c3"><div class="bkct" style="width:154px">&nbsp;</div></td> <td class="c3"><div class="bkct" style="width:154px">&nbsp;</div></td>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">26,900 ops/sec</td> <td class="c2">48,600 ops/sec</td>
<td class="c3"><div class="bsql" style="width:12px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:22px">&nbsp;</div></td>
</table> </table>
<h3>D. Random Writes</h3> <h3>D. Random Writes</h3>
<table class="bn bnbase"> <table class="bn bnbase">
@ -166,8 +166,8 @@ parameters are varied. For the baseline:</p>
<td class="c2">88,500 ops/sec</td> <td class="c2">88,500 ops/sec</td>
<td class="c3"><div class="bkct" style="width:188px">&nbsp;</div></td> <td class="c3"><div class="bkct" style="width:188px">&nbsp;</div></td>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">420 ops/sec</td> <td class="c2">9,860 ops/sec</td>
<td class="c3"><div class="bsql" style="width:1px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:21px">&nbsp;</div></td>
</table> </table>
<p>LevelDB outperforms both SQLite3 and TreeDB in sequential and random write operations and sequential read operations. Kyoto Cabinet has the fastest random read operations.</p> <p>LevelDB outperforms both SQLite3 and TreeDB in sequential and random write operations and sequential read operations. Kyoto Cabinet has the fastest random read operations.</p>
@ -178,26 +178,26 @@ parameters are varied. For the baseline:</p>
<h4>Sequential Writes</h4> <h4>Sequential Writes</h4>
<table class="bn bnbase"> <table class="bn bnbase">
<tr><td class="c1">LevelDB</td> <tr><td class="c1">LevelDB</td>
<td class="c2">1,060 ops/sec</td> <td class="c2">1,100 ops/sec</td>
<td class="c3"><div class="bldb" style="width:127px">&nbsp;</div></td></tr> <td class="c3"><div class="bldb" style="width:234px">&nbsp;</div></td></tr>
<tr><td class="c1">Kyoto TreeDB</td> <tr><td class="c1">Kyoto TreeDB</td>
<td class="c2">1,020 ops/sec</td> <td class="c2">1,000 ops/sec</td>
<td class="c3"><div class="bkct" style="width:122px">&nbsp;</div></td></tr> <td class="c3"><div class="bkct" style="width:224px">&nbsp;</div></td></tr>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">2,910 ops/sec</td> <td class="c2">1,600 ops/sec</td>
<td class="c3"><div class="bsql" style="width:350px">&nbsp;</div></td></tr> <td class="c3"><div class="bsql" style="width:350px">&nbsp;</div></td></tr>
</table> </table>
<h4>Random Writes</h4> <h4>Random Writes</h4>
<table class="bn bnbase"> <table class="bn bnbase">
<tr><td class="c1">LevelDB</td> <tr><td class="c1">LevelDB</td>
<td class="c2">480 ops/sec</td> <td class="c2">480 ops/sec</td>
<td class="c3"><div class="bldb" style="width:77px">&nbsp;</div></td></tr> <td class="c3"><div class="bldb" style="width:105px">&nbsp;</div></td></tr>
<tr><td class="c1">Kyoto TreeDB</td> <tr><td class="c1">Kyoto TreeDB</td>
<td class="c2">1,100 ops/sec</td> <td class="c2">1,100 ops/sec</td>
<td class="c3"><div class="bkct" style="width:350px">&nbsp;</div></td></tr> <td class="c3"><div class="bkct" style="width:240px">&nbsp;</div></td></tr>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">2,200 ops/sec</td> <td class="c2">1,600 ops/sec</td>
<td class="c3"><div class="bsql" style="width:175px">&nbsp;</div></td></tr> <td class="c3"><div class="bsql" style="width:350px">&nbsp;</div></td></tr>
</table> </table>
<p>LevelDB doesn't perform as well with large values of 100,000 bytes each. This is because LevelDB writes keys and values at least twice: first time to the transaction log, and second time (during a compaction) to a sorted file. <p>LevelDB doesn't perform as well with large values of 100,000 bytes each. This is because LevelDB writes keys and values at least twice: first time to the transaction log, and second time (during a compaction) to a sorted file.
With larger values, LevelDB's per-operation efficiency is swamped by the With larger values, LevelDB's per-operation efficiency is swamped by the
@ -211,9 +211,9 @@ cost of extra copies of large values.</p>
<td class="c3"><div class="bldb" style="width:350px">&nbsp;</div></td> <td class="c3"><div class="bldb" style="width:350px">&nbsp;</div></td>
<td class="c4">(1.08x baseline)</td></tr> <td class="c4">(1.08x baseline)</td></tr>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">100,000 entries/sec</td> <td class="c2">124,000 entries/sec</td>
<td class="c3"><div class="bsql" style="width:43px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:52px">&nbsp;</div></td>
<td class="c4">(3.72x baseline)</td></tr> <td class="c4">(2.55x baseline)</td></tr>
</table> </table>
<h4>Random Writes</h4> <h4>Random Writes</h4>
<table class="bn"> <table class="bn">
@ -222,22 +222,20 @@ cost of extra copies of large values.</p>
<td class="c3"><div class="bldb" style="width:350px">&nbsp;</div></td> <td class="c3"><div class="bldb" style="width:350px">&nbsp;</div></td>
<td class="c4">(1.35x baseline)</td></tr> <td class="c4">(1.35x baseline)</td></tr>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">1,000 entries/sec</td> <td class="c2">22,000 entries/sec</td>
<td class="c3"><div class="bsql" style="width:2px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:34px">&nbsp;</div></td>
<td class="c4">(2.38x baseline)</td></tr> <td class="c4">(2.23x baseline)</td></tr>
</table> </table>
<p>Because of the way LevelDB persistent storage is organized, batches of <p>Because of the way LevelDB persistent storage is organized, batches of
random writes are not much slower (only a factor of 4x) than batches random writes are not much slower (only a factor of 4x) than batches
of sequential writes. However SQLite3 sees a significant slowdown of sequential writes.</p>
(factor of 100x) when switching from sequential to random batch
writes. This is because each random batch write in SQLite3 has to
update approximately as many pages as there are keys in the batch.</p>
<h3>C. Synchronous Writes</h3> <h3>C. Synchronous Writes</h3>
<p>In the following benchmark, we enable the synchronous writing modes <p>In the following benchmark, we enable the synchronous writing modes
of all of the databases. Since this change significantly slows down the of all of the databases. Since this change significantly slows down the
benchmark, we stop after 10,000 writes.</p> benchmark, we stop after 10,000 writes. For synchronous write tests, we've
disabled hard drive write-caching (using `hdparm -W 0 [device]`).</p>
<ul> <ul>
<li>For LevelDB, we set WriteOptions.sync = true.</li> <li>For LevelDB, we set WriteOptions.sync = true.</li>
<li>In TreeDB, we enabled TreeDB's OAUTOSYNC option.</li> <li>In TreeDB, we enabled TreeDB's OAUTOSYNC option.</li>
@ -246,32 +244,32 @@ benchmark, we stop after 10,000 writes.</p>
<h4>Sequential Writes</h4> <h4>Sequential Writes</h4>
<table class="bn"> <table class="bn">
<tr><td class="c1">LevelDB</td> <tr><td class="c1">LevelDB</td>
<td class="c2">2,400 ops/sec</td> <td class="c2">100 ops/sec</td>
<td class="c3"><div class="bldb" style="width:350px">&nbsp;</div></td> <td class="c3"><div class="bldb" style="width:350px">&nbsp;</div></td>
<td class="c4">(0.003x baseline)</td></tr> <td class="c4">(0.003x baseline)</td></tr>
<tr><td class="c1">Kyoto TreeDB</td> <tr><td class="c1">Kyoto TreeDB</td>
<td class="c2">140 ops/sec</td> <td class="c2">7 ops/sec</td>
<td class="c3"><div class="bkct" style="width:21px">&nbsp;</div></td> <td class="c3"><div class="bkct" style="width:27px">&nbsp;</div></td>
<td class="c4">(0.0004x baseline)</td></tr> <td class="c4">(0.0004x baseline)</td></tr>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">430 ops/sec</td> <td class="c2">88 ops/sec</td>
<td class="c3"><div class="bsql" style="width:61px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:315px">&nbsp;</div></td>
<td class="c4">(0.016x baseline)</td></tr> <td class="c4">(0.002x baseline)</td></tr>
</table> </table>
<h4>Random Writes</h4> <h4>Random Writes</h4>
<table class="bn"> <table class="bn">
<tr><td class="c1">LevelDB</td> <tr><td class="c1">LevelDB</td>
<td class="c2">2,400 ops/sec</td> <td class="c2">100 ops/sec</td>
<td class="c3"><div class="bldb" style="width:350px">&nbsp;</div></td> <td class="c3"><div class="bldb" style="width:350px">&nbsp;</div></td>
<td class="c4">(0.015x baseline)</td></tr> <td class="c4">(0.015x baseline)</td></tr>
<tr><td class="c1">Kyoto TreeDB</td> <tr><td class="c1">Kyoto TreeDB</td>
<td class="c2">100 ops/sec</td> <td class="c2">8 ops/sec</td>
<td class="c3"><div class="bkct" style="width:14px">&nbsp;</div></td> <td class="c3"><div class="bkct" style="width:29px">&nbsp;</div></td>
<td class="c4">(0.001x baseline)</td></tr> <td class="c4">(0.001x baseline)</td></tr>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">110 ops/sec</td> <td class="c2">88 ops/sec</td>
<td class="c3"><div class="bsql" style="width:16px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:314px">&nbsp;</div></td>
<td class="c4">(0.26x baseline)</td></tr> <td class="c4">(0.009x baseline)</td></tr>
</table> </table>
<p>Also see the <code>ext4</code> performance numbers below <p>Also see the <code>ext4</code> performance numbers below
@ -300,8 +298,8 @@ its baseline measurements):</p>
<td class="c3"><div class="bkct" style="width:239px">&nbsp;</div></td> <td class="c3"><div class="bkct" style="width:239px">&nbsp;</div></td>
<td class="c4">(1.42x baseline)</td></tr> <td class="c4">(1.42x baseline)</td></tr>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">26,900 ops/sec</td> <td class="c2">48,600 ops/sec</td>
<td class="c3"><div class="bsql" style="width:13px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:29px">&nbsp;</div></td>
<td class="c4">(1.00x baseline)</td></tr> <td class="c4">(1.00x baseline)</td></tr>
</table> </table>
<h4>Random Writes</h4> <h4>Random Writes</h4>
@ -315,8 +313,8 @@ its baseline measurements):</p>
<td class="c3"><div class="bkct" style="width:350px">&nbsp;</div></td> <td class="c3"><div class="bkct" style="width:350px">&nbsp;</div></td>
<td class="c4">(1.80x baseline)</td></tr> <td class="c4">(1.80x baseline)</td></tr>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">420 ops/sec</td> <td class="c2">9,860 ops/sec</td>
<td class="c3"><div class="bsql" style="width:1px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:22px">&nbsp;</div></td>
<td class="c4">(1.00x baseline)</td></tr> <td class="c4">(1.00x baseline)</td></tr>
</table> </table>
@ -342,9 +340,9 @@ LevelDB's compression library (Snappy).<p>
<td class="c3"><div class="bkct" style="width:138px">&nbsp;</div></td> <td class="c3"><div class="bkct" style="width:138px">&nbsp;</div></td>
<td class="c4">(0.94x baseline)</td></tr> <td class="c4">(0.94x baseline)</td></tr>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">26,200 ops/sec</td> <td class="c2">48,500 ops/sec</td>
<td class="c3"><div class="bsql" style="width:11px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:21px">&nbsp;</div></td>
<td class="c4">(0.97x baseline)</td></tr> <td class="c4">(1.00x baseline)</td></tr>
</table> </table>
<h4>Random Writes</h4> <h4>Random Writes</h4>
<table class="bn"> <table class="bn">
@ -357,9 +355,9 @@ LevelDB's compression library (Snappy).<p>
<td class="c3"><div class="bkct" style="width:280px">&nbsp;</div></td> <td class="c3"><div class="bkct" style="width:280px">&nbsp;</div></td>
<td class="c4">(3.21x baseline)</td></tr> <td class="c4">(3.21x baseline)</td></tr>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">450 ops/sec</td> <td class="c2">9,670 ops/sec</td>
<td class="c3"><div class="bsql" style="width:0px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:10px">&nbsp;</div></td>
<td class="c4">(1.07x baseline)</td></tr> <td class="c4">(0.98x baseline)</td></tr>
</table> </table>
<p>SQLite's performance does not change substantially when compared to <p>SQLite's performance does not change substantially when compared to
@ -388,9 +386,9 @@ MB.</p>
<td class="c3"><div class="bkct" style="width:72px">&nbsp;</div></td> <td class="c3"><div class="bkct" style="width:72px">&nbsp;</div></td>
<td class="c4">(1.06x baseline)</td></tr> <td class="c4">(1.06x baseline)</td></tr>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">221,000 ops/sec</td> <td class="c2">210,000 ops/sec</td>
<td class="c3"><div class="bsql" style="width:15px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:14px">&nbsp;</div></td>
<td class="c4">(1.19x baseline)</td></tr> <td class="c4">(1.20x baseline)</td></tr>
</table> </table>
<h4>Random Reads</h4> <h4>Random Reads</h4>
@ -404,9 +402,9 @@ MB.</p>
<td class="c3"><div class="bkct" style="width:350px">&nbsp;</div></td> <td class="c3"><div class="bkct" style="width:350px">&nbsp;</div></td>
<td class="c4">(3.07x baseline)</td></tr> <td class="c4">(3.07x baseline)</td></tr>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">197,000 ops/sec</td> <td class="c2">186,000 ops/sec</td>
<td class="c3"><div class="bsql" style="width:149px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:141px">&nbsp;</div></td>
<td class="c4">(1.35x baseline)</td></tr> <td class="c4">(1.39x baseline)</td></tr>
</table> </table>
<p>As expected, the read performance of all of the databases increases <p>As expected, the read performance of all of the databases increases
@ -427,7 +425,7 @@ database.</p>
<td class="c3"><div class="bkct" style="width:88px">&nbsp;</div></td> <td class="c3"><div class="bkct" style="width:88px">&nbsp;</div></td>
<td class="c4">(3.60x baseline)</td></tr> <td class="c4">(3.60x baseline)</td></tr>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">186,000 ops/sec</td> <td class="c2">174,000 ops/sec</td>
<td class="c3"><div class="bsql" style="width:13px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:13px">&nbsp;</div></td>
<td class="c4">(1.00x baseline)</td></tr> <td class="c4">(1.00x baseline)</td></tr>
</table> </table>
@ -442,8 +440,8 @@ database.</p>
<td class="c3"><div class="bkct" style="width:350px">&nbsp;</div></td> <td class="c3"><div class="bkct" style="width:350px">&nbsp;</div></td>
<td class="c4">(1.16x baseline)</td></tr> <td class="c4">(1.16x baseline)</td></tr>
<tr><td class="c1">SQLite3</td> <tr><td class="c1">SQLite3</td>
<td class="c2">146,000 ops/sec</td> <td class="c2">134,000 ops/sec</td>
<td class="c3"><div class="bsql" style="width:292px">&nbsp;</div></td> <td class="c3"><div class="bsql" style="width:268px">&nbsp;</div></td>
<td class="c4">(1.00x baseline)</td></tr> <td class="c4">(1.00x baseline)</td></tr>
</table> </table>
@ -453,7 +451,7 @@ performance may very well be better with compression if it allows more
of the working set to fit in memory.</p> of the working set to fit in memory.</p>
<h2>Note about Ext4 Filesystems</h2> <h2>Note about Ext4 Filesystems</h2>
<p>The preceding numbers are for an ext3 file system. Synchronous writes are much slower under <a href="http://en.wikipedia.org/wiki/Ext4">ext4</a> (LevelDB drops to ~34 writes / second, TreeDB drops to ~5 writes / second; SQLite3 drops to ~24 writes / second) due to ext4's different handling of <span class="code">fsync</span> / <span class="code">msync</span> calls. Even LevelDB's asynchronous write performance drops somewhat since it spreads its storage across multiple files and issues <span class="code">fsync</span> calls when switching to a new file.</p> <p>The preceding numbers are for an ext3 file system. Synchronous writes are much slower under <a href="http://en.wikipedia.org/wiki/Ext4">ext4</a> (LevelDB drops to ~31 writes / second and TreeDB drops to ~5 writes / second; SQLite3's synchronous writes do not noticeably drop) due to ext4's different handling of <span class="code">fsync</span> / <span class="code">msync</span> calls. Even LevelDB's asynchronous write performance drops somewhat since it spreads its storage across multiple files and issues <span class="code">fsync</span> calls when switching to a new file.</p>
<h2>Acknowledgements</h2> <h2>Acknowledgements</h2>
<p>Jeff Dean and Sanjay Ghemawat wrote LevelDB. Kevin Tseng wrote and compiled these benchmarks. Mikio Hirabayashi, Scott Hess, and Gabor Cselle provided help and advice.</p> <p>Jeff Dean and Sanjay Ghemawat wrote LevelDB. Kevin Tseng wrote and compiled these benchmarks. Mikio Hirabayashi, Scott Hess, and Gabor Cselle provided help and advice.</p>