2/28/2024 0 Comments Sqlite vs mysql![]() INSERT INTO t3 VALUES(25000,84791,'eighty four thousand seven hundred ninety one') INSERT INTO t3 VALUES(24999,88509,'eighty eight thousand five hundred nine') Test 3: 25000 INSERTs into an indexed tableĬREATE TABLE t3(a INTEGER, b INTEGER, c VARCHAR(100)) This way, SQLite is much faster than either PostgreSQL and MySQL. Have to do any fsync()s until the very end. When all the INSERTs are put in a transaction, SQLite no longer has toĬlose and reopen the database or invalidate its cache between each statement. INSERT INTO t2 VALUES(25000,94666,'ninety four thousand six hundred sixty six') INSERT INTO t2 VALUES(24999,89569,'eighty nine thousand five hundred sixty nine') INSERT INTO t2 VALUES(1,59672,'fifty nine thousand six hundred seventy two') Test 2: 25000 INSERTs in a transactionĬREATE TABLE t2(a INTEGER, b INTEGER, c VARCHAR(100)) Synchronous test, SQLite was sitting idle waiting on disk I/O to complete. SQLite calls fsync() afterĮach synchronous transaction to make sure that all data is safely on Version of SQLite is still nearly as fast as MySQL. Is a separate transaction so the database file must be opened and closedĪnd the cache must be flushed 1000 times. SQLite must close and reopen the database file, and thus invalidate INSERT INTO t1 VALUES(1000,94142,'ninety four thousand one hundred forty two') īecause it does not have a central server to coordinate access, INSERT INTO t1 VALUES(999,24322,'twenty four thousand three hundred twenty two') INSERT INTO t1 VALUES(998,66289,'sixty six thousand two hundred eighty nine') INSERT INTO t1 VALUES(2,75560,'seventy five thousand five hundred sixty') INSERT INTO t1 VALUES(1,13153,'thirteen thousand one hundred fifty three') Synchronous) and the asynchronous SQLite times are forĬomparison against the asynchronous MySQL engine.ĬREATE TABLE t1(a INTEGER, b INTEGER, c VARCHAR(100)) Times are for comparison against PostgreSQL (which is also Generally speaking, the synchronous SQLite ![]() Operating system crash or an unexpected power failure couldĭamage the database. SQLite is sometimes much faster, but there is a risk that an Operating system crashes or the computer powers down unexpectedly Is necessary to guarantee the integrity of the database if the With synchronization turnedĪn fsync() system call (or the equivalent) at key pointsĪctually been written to the disk drive surface. The first value is for SQLite in its default configuration withįull disk synchronization turned on. Two separate time values are reported for SQLite. The times reported on all tests represent wall-clock time The -DNDEBUG=1 compiler option roughly doublesĪll tests are conducted on an otherwise quiescent machine.Ī simple Tcl script was used to generate and run all the tests.Ī copy of this Tcl script can be found in the SQLite source tree The -DNDEBUG=1 switch which disables the many "assert()" statements It was compiled with -O6 optimization and with SQLite was tested in the same configuration that it appears PostgreSQL and MySQL run at about the same speed. Matt Sergeant reports that he has tuned his PostgreSQL installationĪnd rerun the tests shown below. Work on a machine with 8MB of RAM) and that PostgreSQL couldīe made to run a lot faster with some knowledgeable configuration Is unnecessarily conservative (it is designed to I am told that the default PostgreSQL configuration in RedHat 7.3 Not having to support transactions gives MySQL aīig speed advantage, but SQLite is still able to hold its own on most The default MySQL configuration on RedHat 7.2 does not support No effort was made to tune these engines. (PostgreSQL version 7.1.3 and MySQL version 3.23.41.) The PostgreSQL and MySQL servers used were as delivered by default on The operating system is RedHat Linux 7.2 with ![]() The platform used for these tests is a 1.6GHz Athlon with 1GB or memoryĪnd an IDE disk drive. They do not measure how well the database engines scale to larger problems. These tests are on a relatively small (approximately 14 megabyte) database. Optimization of complex queries involving multiple joins and subqueries. These tests did not attempt to measure multi-user performance or The results presented here come with the following caveats: SQLite works best if you group multiple operations together into But this is not seen as a problem because SQLite does not execute CREATE INDEX or DROP TABLE as fast as More than twice as fast) than MySQL 3.23.41 On RedHat 7.2 for most common operations. SQLite 2.7.6 is significantly faster (sometimes as much as 10 orĢ0 times faster) than the default PostgreSQL 7.1.3 installation SQLite 2.7.6, PostgreSQL 7.1.3, and MySQL 3.23.41.Ĭonclusions drawn from these experiments: This page has been retained onlyĪ series of tests were run to measure the relative performance of The numbers here have become meaningless. It describes a speed comparison betweenĪrchaic versions of SQLite, MySQL and PostgreSQL.
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