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Overview
| Comment: | Update the speed.html documentation. Recent optimizations have made the library much faster. (CVS 846) |
|---|---|
| Downloads: | Tarball | ZIP archive | SQL archive |
| Timelines: | family | ancestors | descendants | both | trunk |
| Files: | files | file ages | folders |
| SHA1: | ed47d162a072a2f98b633cc14f2be147 |
| User & Date: | drh 2003-01-25 14:25:42 |
Context
|
2003-01-25
| ||
| 14:32 | Preparations for the release of version 2.7.6. (CVS 847) check-in: 5143d481 user: drh tags: trunk | |
| 14:25 | Update the speed.html documentation. Recent optimizations have made the library much faster. (CVS 846) check-in: ed47d162 user: drh tags: trunk | |
|
2003-01-24
| ||
| 12:14 | Add asserts to btree.c that check for the correct size of various typedefs and structures. Ticket #233. (CVS 845) check-in: c7e647d0 user: drh tags: trunk | |
Changes
Changes to www/speed.tcl.
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#
# Run this Tcl script to generate the speed.html file.
#
set rcsid {$Id: speed.tcl,v 1.9 2003/01/18 22:01:07 drh Exp $ }
puts {<html>
<head>
<title>Database Speed Comparison: SQLite versus PostgreSQL</title>
</head>
<body bgcolor=white>
<h1 align=center>
................................................................................
<ul>
<li><p>
SQLite 2.7.6 is significantly faster (sometimes as much as 10 or
20 times faster) than PostgreSQL 7.1.3
for most common operations.
</p></li>
<li><p>
SQLite 2.7.6 is usually faster than MySQL 3.23.41 (sometimes
more than twice as fast) though for some operations such as
full table scans, it can be as much as 30% slower.
</p></li>
<li><p>
SQLite does not execute CREATE INDEX or DROP TABLE as fast as
the other databases. But this as not seen is a problem because
those are infrequent operations.
</p></li>
</ul>
<p>
The results presented here come with the following caveats:
</p>
<ul>
<li><p>
These tests did not attempt to measure multi-user performance or
optimization of complex queries involving multiple joins and subqueries.
</p></li>
<li><p>
These tests are on a relatively small (approximately 10 megabyte) database.
They do not measure how well the database engines scale to larger problems.
</p></li>
</ul>
<h2>Test Environment</h2>
<p>
................................................................................
INSERT INTO t1 VALUES(2,75560,'seventy five thousand five hundred sixty');<br>
<i>... 995 lines omitted</i><br>
INSERT INTO t1 VALUES(998,66289,'sixty six thousand two hundred eighty nine');<br>
INSERT INTO t1 VALUES(999,24322,'twenty four thousand three hundred twenty two');<br>
INSERT INTO t1 VALUES(1000,94142,'ninety four thousand one hundred forty two');<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 3.658</td></tr>
<tr><td>MySQL:</td><td align="right"> 0.109</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 7.177</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.266</td></tr>
</table>
<p>SQLite must close and reopen the database file, and thus invalidate
its cache, for each SQL statement. In spite of this, the asynchronous
version of SQLite is still nearly as fast as MySQL. Notice how much slower
the synchronous version is, however. This is due to the necessity of
calling <b>fsync()</b> after each SQL statement.</p>
<h2>Test 2: 25000 INSERTs in a transaction</h2>
<blockquote>
BEGIN;<br>
CREATE TABLE t2(a INTEGER, b INTEGER, c VARCHAR(100));<br>
INSERT INTO t2 VALUES(1,298361,'two hundred ninety eight thousand three hundred sixty one');<br>
<i>... 24997 lines omitted</i><br>
INSERT INTO t2 VALUES(24999,447847,'four hundred forty seven thousand eight hundred forty seven');<br>
INSERT INTO t2 VALUES(25000,473330,'four hundred seventy three thousand three hundred thirty');<br>
COMMIT;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 5.058</td></tr>
<tr><td>MySQL:</td><td align="right"> 2.271</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 0.912</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.798</td></tr>
</table>
<p>
When all the INSERTs are put in a transaction, SQLite no longer has to
close and reopen the database between each statement. It also does not
have to do any fsync()s until the very end. When unshackled in
this way, SQLite is much faster than either PostgreSQL and MySQL.
</p>
<h2>Test 3: 100 SELECTs without an index</h2>
<blockquote>
BEGIN;<br>
SELECT count(*), avg(b) FROM t2 WHERE b>=0 AND b<1000;<br>
SELECT count(*), avg(b) FROM t2 WHERE b>=100 AND b<1100;<br>
<i>... 96 lines omitted</i><br>
SELECT count(*), avg(b) FROM t2 WHERE b>=9800 AND b<10800;<br>
SELECT count(*), avg(b) FROM t2 WHERE b>=9900 AND b<10900;<br>
COMMIT;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 3.657</td></tr>
<tr><td>MySQL:</td><td align="right"> 3.368</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 4.386</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 4.314</td></tr>
</table>
<p>
This test does 100 queries on a 25000 entry table without an index,
thus requiring a full table scan. SQLite is about 20% or 30% slower
than PostgreSQL and MySQL. The reason for this is believed to be
because SQLite stores all data as strings
and must therefore do 5 million string-to-number conversions in the
course of evaluating the WHERE clauses. Both PostgreSQL and MySQL
store data as binary values where appropriate and can forego
this conversion effort.
</p>
<h2>Test 4: 100 SELECTs on a string comparison</h2>
<blockquote>
BEGIN;<br>
SELECT count(*), avg(b) FROM t2 WHERE c LIKE '%one%';<br>
SELECT count(*), avg(b) FROM t2 WHERE c LIKE '%two%';<br>
<i>... 96 lines omitted</i><br>
SELECT count(*), avg(b) FROM t2 WHERE c LIKE '%ninety nine%';<br>
SELECT count(*), avg(b) FROM t2 WHERE c LIKE '%one hundred%';<br>
COMMIT;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 15.967</td></tr>
<tr><td>MySQL:</td><td align="right"> 5.088</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 5.419</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 5.367</td></tr>
</table>
<p>
This test still does 100 full table scans but it uses
uses string comparisons instead of numerical comparisions.
SQLite is almost three times faster than PostgreSQL here. But it is
still 15% slower than MySQL. MySQL appears to be very good
at doing full table scans.
</p>
<h2>Test 5: Creating an index</h2>
<blockquote>
CREATE INDEX i2a ON t2(a);<br>CREATE INDEX i2b ON t2(b);
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 0.431</td></tr>
<tr><td>MySQL:</td><td align="right"> 0.340</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 0.814</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.675</td></tr>
</table>
<p>
SQLite is slower at creating new indices. But since creating
new indices is an uncommon operation, this is not seen as a
problem.
</p>
<h2>Test 6: 5000 SELECTs with an index</h2>
<blockquote>
SELECT count(*), avg(b) FROM t2 WHERE b>=0 AND b<100;<br>
SELECT count(*), avg(b) FROM t2 WHERE b>=100 AND b<200;<br>
SELECT count(*), avg(b) FROM t2 WHERE b>=200 AND b<300;<br>
<i>... 4994 lines omitted</i><br>
SELECT count(*), avg(b) FROM t2 WHERE b>=499700 AND b<499800;<br>
SELECT count(*), avg(b) FROM t2 WHERE b>=499800 AND b<499900;<br>
SELECT count(*), avg(b) FROM t2 WHERE b>=499900 AND b<500000;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 5.369</td></tr>
<tr><td>MySQL:</td><td align="right"> 1.489</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 1.423</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 1.358</td></tr>
</table>
<p>
This test runs a set of 5000 queries that are similar in form to
those in test 3. But now instead of being slower, SQLite
is faster than both PostgreSQL and MySQL.
</p>
<h2>Test 7: 1000 UPDATEs without an index</h2>
<blockquote>
BEGIN;<br>
UPDATE t1 SET b=b*2 WHERE a>=0 AND a<10;<br>
UPDATE t1 SET b=b*2 WHERE a>=10 AND a<20;<br>
<i>... 996 lines omitted</i><br>
UPDATE t1 SET b=b*2 WHERE a>=9980 AND a<9990;<br>
UPDATE t1 SET b=b*2 WHERE a>=9990 AND a<10000;<br>
COMMIT;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 1.740</td></tr>
<tr><td>MySQL:</td><td align="right"> 8.162</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 0.635</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.608</td></tr>
</table>
<p>
For this particular UPDATE test, MySQL is consistently
five or ten times
slower than PostgreSQL and SQLite. I do not know why. MySQL is
normally a very fast engine. Perhaps this problem has been addressed
in later versions of MySQL.
</p>
<h2>Test 8: 25000 UPDATEs with an index</h2>
<blockquote>
BEGIN;<br>
UPDATE t2 SET b=271822 WHERE a=1;<br>
UPDATE t2 SET b=28304 WHERE a=2;<br>
<i>... 24996 lines omitted</i><br>
UPDATE t2 SET b=442549 WHERE a=24999;<br>
UPDATE t2 SET b=423958 WHERE a=25000;<br>
COMMIT;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 32.118</td></tr>
<tr><td>MySQL:</td><td align="right"> 8.132</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 4.109</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 3.712</td></tr>
</table>
<p>
As recently as version 2.7.0, SQLite ran at about the same speed as
MySQL on this test. But recent optimizations to SQLite have doubled
speed of UPDATEs.
</p>
<h2>Test 9: 25000 text UPDATEs with an index</h2>
<blockquote>
BEGIN;<br>
UPDATE t2 SET c='four hundred sixty eight thousand twenty six' WHERE a=1;<br>
UPDATE t2 SET c='one hundred twenty one thousand nine hundred twenty eight' WHERE a=2;<br>
<i>... 24996 lines omitted</i><br>
UPDATE t2 SET c='thirty five thousand sixty five' WHERE a=24999;<br>
UPDATE t2 SET c='three hundred forty seven thousand three hundred ninety three' WHERE a=25000;<br>
COMMIT;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 55.309</td></tr>
<tr><td>MySQL:</td><td align="right"> 6.585</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 2.474</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 1.800</td></tr>
</table>
<p>
Here again, version 2.7.0 of SQLite used to run at about the same speed
as MySQL. But now version 2.7.6 is over two times faster than MySQL and
over twenty times faster than PostgreSQL.
</p>
<h2>Test 10: INSERTs from a SELECT</h2>
<blockquote>
BEGIN;<br>INSERT INTO t1 SELECT b,a,c FROM t2;<br>INSERT INTO t2 SELECT b,a,c FROM t1;<br>COMMIT;
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 58.956</td></tr>
<tr><td>MySQL:</td><td align="right"> 1.465</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 2.926</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 1.664</td></tr>
</table>
<p>
The poor performance of PostgreSQL in this case appears to be due to its
synchronous behavior. The CPU was mostly idle the test run. Presumably,
PostgreSQL was spending most of its time waiting on disk I/O to complete.
I'm not sure why SQLite performs poorly here. It use to be quicker at this
test, but the same enhancements that sped up the UPDATE logic seem to have
slowed down this test.
</p>
<h2>Test 11: DELETE without an index</h2>
<blockquote>
DELETE FROM t2 WHERE c LIKE '%fifty%';
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 1.365</td></tr>
<tr><td>MySQL:</td><td align="right"> 0.849</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 4.005</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.631</td></tr>
</table>
<p>
The synchronous version of SQLite is the slowest of the group in this test,
but the asynchronous version is the fastest. SQLite used about the same
amount of CPU time in both versions; the difference is the extra time needed
to write information to the disk surface.
</p>
<h2>Test 12: DELETE with an index</h2>
<blockquote>
DELETE FROM t2 WHERE a>10 AND a<20000;
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 1.340</td></tr>
<tr><td>MySQL:</td><td align="right"> 2.167</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 2.344</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.858</td></tr>
</table>
<p>
This test is significant because it is one of the few where
PostgreSQL is faster than MySQL. The asynchronous SQLite is,
however, faster then both the other two.
</p>
</table>
<h2>Test 13: A big INSERT after a big DELETE</h2>
<blockquote>
INSERT INTO t2 SELECT * FROM t1;
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 12.672</td></tr>
<tr><td>MySQL:</td><td align="right"> 1.837</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 3.076</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 1.570</td></tr>
</table>
<p>
Some older versions of SQLite would show decreasing performance after a
sequence DELETEs followed by new INSERTs. As this test shows, the
problem has now been resolved.
</p>
<h2>Test 14: A big DELETE followed by many small INSERTs</h2>
<blockquote>
BEGIN;<br>
DELETE FROM t1;<br>
INSERT INTO t1 VALUES(1,29676,'twenty nine thousand six hundred seventy six');<br>
<i>... 11997 lines omitted</i><br>
INSERT INTO t1 VALUES(11999,71818,'seventy one thousand eight hundred eighteen');<br>
INSERT INTO t1 VALUES(12000,58579,'fifty eight thousand five hundred seventy nine');<br>
COMMIT;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 4.165</td></tr>
<tr><td>MySQL:</td><td align="right"> 1.733</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 0.652</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.465</td></tr>
</table>
<p>
SQLite is very good at doing INSERTs within a transaction, which probably
explains why it is so much faster than the other databases at this test.
</p>
<h2>Test 15: DROP TABLE</h2>
<blockquote>
DROP TABLE t1;<br>DROP TABLE t2;
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 0.133</td></tr>
<tr><td>MySQL:</td><td align="right"> 0.014</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 0.873</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.224</td></tr>
</table>
<p>
SQLite is slower than the other databases when it comes to dropping tables.
This probably is because when SQLite drops a table, it has to go through and
erase the records in the database file that deal with that table. MySQL and
PostgreSQL, on the other hand, use separate files to represent each table
|
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#
# Run this Tcl script to generate the speed.html file.
#
set rcsid {$Id: speed.tcl,v 1.10 2003/01/25 14:25:42 drh Exp $ }
puts {<html>
<head>
<title>Database Speed Comparison: SQLite versus PostgreSQL</title>
</head>
<body bgcolor=white>
<h1 align=center>
................................................................................
<ul>
<li><p>
SQLite 2.7.6 is significantly faster (sometimes as much as 10 or
20 times faster) than PostgreSQL 7.1.3
for most common operations.
</p></li>
<li><p>
SQLite 2.7.6 is often faster (sometimes
more than twice as fast) than MySQL 3.23.41
for most common operations.
</p></li>
<li><p>
SQLite does not execute CREATE INDEX or DROP TABLE as fast as
the other databases. But this as not seen is a problem because
those are infrequent operations.
</p></li>
<li><p>
SQLite works best if you group multiple operations together into
a single transaction.
</p></li>
</ul>
<p>
The results presented here come with the following caveats:
</p>
<ul>
<li><p>
These tests did not attempt to measure multi-user performance or
optimization of complex queries involving multiple joins and subqueries.
</p></li>
<li><p>
These tests are on a relatively small (approximately 14 megabyte) database.
They do not measure how well the database engines scale to larger problems.
</p></li>
</ul>
<h2>Test Environment</h2>
<p>
................................................................................
INSERT INTO t1 VALUES(2,75560,'seventy five thousand five hundred sixty');<br>
<i>... 995 lines omitted</i><br>
INSERT INTO t1 VALUES(998,66289,'sixty six thousand two hundred eighty nine');<br>
INSERT INTO t1 VALUES(999,24322,'twenty four thousand three hundred twenty two');<br>
INSERT INTO t1 VALUES(1000,94142,'ninety four thousand one hundred forty two');<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 4.373</td></tr>
<tr><td>MySQL:</td><td align="right"> 0.114</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 13.061</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.223</td></tr>
</table>
<p>
Because it does not have a central server to coordinate access,
SQLite must close and reopen the database file, and thus invalidate
its cache, for each transaction. In this test, each SQL statement
is a separate transaction so the database file must be opened and closed
and the cache must be flushed 1000 times. In spite of this, the asynchronous
version of SQLite is still nearly as fast as MySQL. Notice how much slower
the synchronous version is, however. SQLite calls <b>fsync()</b> after
each synchronous transaction to make sure that all data is safely on
the disk surface before continuing. For most of the 13 seconds in the
synchronous test, SQLite was sitting idle waiting on disk I/O to complete.</p>
<h2>Test 2: 25000 INSERTs in a transaction</h2>
<blockquote>
BEGIN;<br>
CREATE TABLE t2(a INTEGER, b INTEGER, c VARCHAR(100));<br>
INSERT INTO t2 VALUES(1,59672,'fifty nine thousand six hundred seventy two');<br>
<i>... 24997 lines omitted</i><br>
INSERT INTO t2 VALUES(24999,89569,'eighty nine thousand five hundred sixty nine');<br>
INSERT INTO t2 VALUES(25000,94666,'ninety four thousand six hundred sixty six');<br>
COMMIT;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 4.900</td></tr>
<tr><td>MySQL:</td><td align="right"> 2.184</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 0.914</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.757</td></tr>
</table>
<p>
When all the INSERTs are put in a transaction, SQLite no longer has to
close and reopen the database or invalidate its cache between each statement.
It also does not
have to do any fsync()s until the very end. When unshackled in
this way, SQLite is much faster than either PostgreSQL and MySQL.
</p>
<h2>Test 3: 25000 INSERTs into an indexed tablel</h2>
<blockquote>
BEGIN;<br>
CREATE TABLE t3(a INTEGER, b INTEGER, c VARCHAR(100));<br>
CREATE INDEX i3 ON t3(c);<br>
<i>... 24998 lines omitted</i><br>
INSERT INTO t3 VALUES(24999,88509,'eighty eight thousand five hundred nine');<br>
INSERT INTO t3 VALUES(25000,84791,'eighty four thousand seven hundred ninety one');<br>
COMMIT;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 8.175</td></tr>
<tr><td>MySQL:</td><td align="right"> 3.197</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 1.555</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 1.402</td></tr>
</table>
<p>
There were reports that SQLite did not perform as well on an indexed table.
This test was recently added to disprove those rumors. It is true that
SQLite is not as fast at creating new index entries as the other engines
(see Test 6 below) but its overall speed is still better.
</p>
<h2>Test 4: 100 SELECTs without an index</h2>
<blockquote>
BEGIN;<br>
SELECT count(*), avg(b) FROM t2 WHERE b>=0 AND b<1000;<br>
SELECT count(*), avg(b) FROM t2 WHERE b>=100 AND b<1100;<br>
<i>... 96 lines omitted</i><br>
SELECT count(*), avg(b) FROM t2 WHERE b>=9800 AND b<10800;<br>
SELECT count(*), avg(b) FROM t2 WHERE b>=9900 AND b<10900;<br>
COMMIT;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 3.629</td></tr>
<tr><td>MySQL:</td><td align="right"> 2.760</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 2.494</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 2.526</td></tr>
</table>
<p>
This test does 100 queries on a 25000 entry table without an index,
thus requiring a full table scan. Prior versions of SQLite used to
be slower than PostgreSQL and MySQL on this test, but recent performance
enhancements have increased its speed so that it is now the fastest
of the group.
</p>
<h2>Test 5: 100 SELECTs on a string comparison</h2>
<blockquote>
BEGIN;<br>
SELECT count(*), avg(b) FROM t2 WHERE c LIKE '%one%';<br>
SELECT count(*), avg(b) FROM t2 WHERE c LIKE '%two%';<br>
<i>... 96 lines omitted</i><br>
SELECT count(*), avg(b) FROM t2 WHERE c LIKE '%ninety nine%';<br>
SELECT count(*), avg(b) FROM t2 WHERE c LIKE '%one hundred%';<br>
COMMIT;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 13.409</td></tr>
<tr><td>MySQL:</td><td align="right"> 4.640</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 3.362</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 3.372</td></tr>
</table>
<p>
This test still does 100 full table scans but it uses
uses string comparisons instead of numerical comparisions.
SQLite is over three times faster than PostgreSQL here and about 30%
faster than MySQL.
</p>
<h2>Test 6: Creating an index</h2>
<blockquote>
CREATE INDEX i2a ON t2(a);<br>CREATE INDEX i2b ON t2(b);
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 0.381</td></tr>
<tr><td>MySQL:</td><td align="right"> 0.318</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 0.777</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.659</td></tr>
</table>
<p>
SQLite is slower at creating new indices. This is not a huge problem
(since new indices are not created very often) but it is something that
is being worked on. Hopefully, future versions of SQLite will do better
here.
</p>
<h2>Test 7: 5000 SELECTs with an index</h2>
<blockquote>
SELECT count(*), avg(b) FROM t2 WHERE b>=0 AND b<100;<br>
SELECT count(*), avg(b) FROM t2 WHERE b>=100 AND b<200;<br>
SELECT count(*), avg(b) FROM t2 WHERE b>=200 AND b<300;<br>
<i>... 4994 lines omitted</i><br>
SELECT count(*), avg(b) FROM t2 WHERE b>=499700 AND b<499800;<br>
SELECT count(*), avg(b) FROM t2 WHERE b>=499800 AND b<499900;<br>
SELECT count(*), avg(b) FROM t2 WHERE b>=499900 AND b<500000;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 4.614</td></tr>
<tr><td>MySQL:</td><td align="right"> 1.270</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 1.121</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 1.162</td></tr>
</table>
<p>
All three database engines run faster when they have indices to work with.
But SQLite is still the fastest.
</p>
<h2>Test 8: 1000 UPDATEs without an index</h2>
<blockquote>
BEGIN;<br>
UPDATE t1 SET b=b*2 WHERE a>=0 AND a<10;<br>
UPDATE t1 SET b=b*2 WHERE a>=10 AND a<20;<br>
<i>... 996 lines omitted</i><br>
UPDATE t1 SET b=b*2 WHERE a>=9980 AND a<9990;<br>
UPDATE t1 SET b=b*2 WHERE a>=9990 AND a<10000;<br>
COMMIT;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 1.739</td></tr>
<tr><td>MySQL:</td><td align="right"> 8.410</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 0.637</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.638</td></tr>
</table>
<p>
For this particular UPDATE test, MySQL is consistently
five or ten times
slower than PostgreSQL and SQLite. I do not know why. MySQL is
normally a very fast engine. Perhaps this problem has been addressed
in later versions of MySQL.
</p>
<h2>Test 9: 25000 UPDATEs with an index</h2>
<blockquote>
BEGIN;<br>
UPDATE t2 SET b=468026 WHERE a=1;<br>
UPDATE t2 SET b=121928 WHERE a=2;<br>
<i>... 24996 lines omitted</i><br>
UPDATE t2 SET b=35065 WHERE a=24999;<br>
UPDATE t2 SET b=347393 WHERE a=25000;<br>
COMMIT;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 18.797</td></tr>
<tr><td>MySQL:</td><td align="right"> 8.134</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 3.520</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 3.104</td></tr>
</table>
<p>
As recently as version 2.7.0, SQLite ran at about the same speed as
MySQL on this test. But recent optimizations to SQLite have more
than doubled speed of UPDATEs.
</p>
<h2>Test 10: 25000 text UPDATEs with an index</h2>
<blockquote>
BEGIN;<br>
UPDATE t2 SET c='one hundred forty eight thousand three hundred eighty two' WHERE a=1;<br>
UPDATE t2 SET c='three hundred sixty six thousand five hundred two' WHERE a=2;<br>
<i>... 24996 lines omitted</i><br>
UPDATE t2 SET c='three hundred eighty three thousand ninety nine' WHERE a=24999;<br>
UPDATE t2 SET c='two hundred fifty six thousand eight hundred thirty' WHERE a=25000;<br>
COMMIT;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 48.133</td></tr>
<tr><td>MySQL:</td><td align="right"> 6.982</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 2.408</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 1.725</td></tr>
</table>
<p>
Here again, version 2.7.0 of SQLite used to run at about the same speed
as MySQL. But now version 2.7.6 is over two times faster than MySQL and
over twenty times faster than PostgreSQL.
</p>
<p>
In fairness to PostgreSQL, it started thrashing on this test. A
knowledgeable administrator might be able to get PostgreSQL to run a lot
faster here by tweaking and tuning the server a little.
</p>
<h2>Test 11: INSERTs from a SELECT</h2>
<blockquote>
BEGIN;<br>INSERT INTO t1 SELECT b,a,c FROM t2;<br>INSERT INTO t2 SELECT b,a,c FROM t1;<br>COMMIT;
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 61.364</td></tr>
<tr><td>MySQL:</td><td align="right"> 1.537</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 2.787</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 1.599</td></tr>
</table>
<p>
The asynchronous SQLite is just a shade slower than MySQL on this test.
(MySQL seems to be especially adept at INSERT...SELECT statements.)
The PostgreSQL engine is still thrashing - most of the 61 seconds it used
were spent waiting on disk I/O.
</p>
<h2>Test 12: DELETE without an index</h2>
<blockquote>
DELETE FROM t2 WHERE c LIKE '%fifty%';
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 1.509</td></tr>
<tr><td>MySQL:</td><td align="right"> 0.975</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 4.004</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.560</td></tr>
</table>
<p>
The synchronous version of SQLite is the slowest of the group in this test,
but the asynchronous version is the fastest.
The difference is the extra time needed to execute fsync().
</p>
<h2>Test 13: DELETE with an index</h2>
<blockquote>
DELETE FROM t2 WHERE a>10 AND a<20000;
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 1.316</td></tr>
<tr><td>MySQL:</td><td align="right"> 2.262</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 2.068</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.752</td></tr>
</table>
<p>
This test is significant because it is one of the few where
PostgreSQL is faster than MySQL. The asynchronous SQLite is,
however, faster then both the other two.
</p>
<h2>Test 14: A big INSERT after a big DELETE</h2>
<blockquote>
INSERT INTO t2 SELECT * FROM t1;
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 13.168</td></tr>
<tr><td>MySQL:</td><td align="right"> 1.815</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 3.210</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 1.485</td></tr>
</table>
<p>
Some older versions of SQLite (prior to version 2.4.0)
would show decreasing performance after a
sequence of DELETEs followed by new INSERTs. As this test shows, the
problem has now been resolved.
</p>
<h2>Test 15: A big DELETE followed by many small INSERTs</h2>
<blockquote>
BEGIN;<br>
DELETE FROM t1;<br>
INSERT INTO t1 VALUES(1,10719,'ten thousand seven hundred nineteen');<br>
<i>... 11997 lines omitted</i><br>
INSERT INTO t1 VALUES(11999,72836,'seventy two thousand eight hundred thirty six');<br>
INSERT INTO t1 VALUES(12000,64231,'sixty four thousand two hundred thirty one');<br>
COMMIT;<br>
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 4.556</td></tr>
<tr><td>MySQL:</td><td align="right"> 1.704</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 0.618</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.406</td></tr>
</table>
<p>
SQLite is very good at doing INSERTs within a transaction, which probably
explains why it is so much faster than the other databases at this test.
</p>
<h2>Test 16: DROP TABLE</h2>
<blockquote>
DROP TABLE t1;<br>DROP TABLE t2;<br>DROP TABLE t3;
</blockquote><table border=0 cellpadding=0 cellspacing=0>
<tr><td>PostgreSQL:</td><td align="right"> 0.135</td></tr>
<tr><td>MySQL:</td><td align="right"> 0.015</td></tr>
<tr><td>SQLite 2.7.6:</td><td align="right"> 0.939</td></tr>
<tr><td>SQLite 2.7.6 (nosync):</td><td align="right"> 0.254</td></tr>
</table>
<p>
SQLite is slower than the other databases when it comes to dropping tables.
This probably is because when SQLite drops a table, it has to go through and
erase the records in the database file that deal with that table. MySQL and
PostgreSQL, on the other hand, use separate files to represent each table
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