FileSystem & DataBase System
While writing Inklog, I’ve been debating with myself regarding my use of the filesystem as a datastore. While the filesystem certainly makes creating, updating, visualizing, backing up, and restoring data much easier than it would be in a database, it adds many hardships. First of all, the convenience of SQL is thrown out the window. While it is nice that using the filesystem doesn’t require a database server, not being able to use a database server means that more programming is involved. Additionally, things like searching through all the entries in the system become difficult, not to mention slow. Another downfall is that the filesystem limits the amount of metadata for each entry that can be kept in a simple fashion.
However, the biggest question on my mind was whether or not using a database server would be faster or slower when performing the most commonly requested actions: getting a list of recent items from the entire system, getting a list of items from a category, and getting one item. I decided to write a test case.
I created 6000 empty files in 20 directories. I also created a table in a mysql database that simulated the filesystem: name, mtime, dir, data. I added indexes on dir, name, and mtime. Then I started testing. In each case the test is run 10 times. Then the average is displayed. For the database tests, mysql_connect is called each time.
Getting the filenames of the 10 most recent entries from the entire system.
FILESYSTEM
TIME: 1.7814919948578
TIME: 1.7425200939178
TIME: 1.8071219921112
TIME: 1.6778069734573
TIME: 1.6711789369583
TIME: 1.7414019107819
TIME: 1.6959699392319
TIME: 1.6531630754471
TIME: 1.7546479701996
TIME: 1.6758890151978
TOT TIME: 17.201191902161
AVG TIME: 1.5637447183782DATABASE
TIME: 0.0039100646972656
TIME: 0.001039981842041
TIME: 0.00095093250274658
TIME: 0.00096702575683594
TIME: 0.00095295906066895
TIME: 0.00098395347595215
TIME: 0.0009620189666748
TIME: 0.0009760856628418
TIME: 0.00094294548034668
TIME: 0.00095808506011963
TOT TIME: 0.012644052505493
AVG TIME: 0.0011494593186812Getting the filenames of the 10 most recent files in a single directory.
FILESYSTEM
TIME: 0.055459976196289
TIME: 0.053847074508667
TIME: 0.044721961021423
TIME: 0.043873071670532
TIME: 0.043742060661316
TIME: 0.043787956237793
TIME: 0.043717980384827
TIME: 0.04374098777771
TIME: 0.043833017349243
TIME: 0.04370105266571
TOT TIME: 0.46042513847351
AVG TIME: 0.041856830770319DATABASE
TIME: 0.0095839500427246
TIME: 0.0055500268936157
TIME: 0.005547046661377
TIME: 0.0055389404296875
TIME: 0.0056079626083374
TIME: 0.00553297996521
TIME: 0.005499005317688
TIME: 0.0055099725723267
TIME: 0.0053470134735107
TIME: 0.0053049325942993
TOT TIME: 0.059021830558777
AVG TIME: 0.0053656209598888Getting one item.
FILESYSTEM
TIME: 0.00032293796539307
TIME: 0.00021898746490479
TIME: 0.00017297267913818
TIME: 0.00016999244689941
TIME: 0.00027298927307129
TIME: 0.00017201900482178
TIME: 0.00016689300537109
TIME: 0.00016403198242188
TIME: 0.0001760721206665
TIME: 0.00017201900482178
TOT TIME: 0.0020089149475098
AVG TIME: 0.0001826286315918DATABASE
TIME: 0.0042519569396973
TIME: 0.0011199712753296
TIME: 0.0010420083999634
TIME: 0.0010360479354858
TIME: 0.0010439157485962
TIME: 0.0010349750518799
TIME: 0.001041054725647
TIME: 0.0010310411453247
TIME: 0.0010330677032471
TIME: 0.0064520835876465
TOT TIME: 0.019086122512817
AVG TIME: 0.0017351020466198The database was 1360 times faster than the filesystem when looking for the 10 most recent items in the entire system. The database was 7.8 times faster when looking for the 10 most recent items in a single directory. However, the filesystem was 9.5 times faster at getting a single file.
These numbers skew greater and greater towards the database as the number of items increases. And, in the one place that the filesystem wins, the operation being performed is so un-time-consuming in general, that the increase in the speed of the filesystem doesn’t amount to much.
These tests were performed with the database being on the same server as the running script. Additionally, the server performing these actions was, basically, not performing anything else at the time. If your database server is only accessible over a 2400bps modem link, your results will differ greatly. Additionally, if your database server is heavily loaded, while your web server isn’t, you may also see very different results.
Benchmarks are crap, for the most part. They don’t really mean a whole lot, unless they represent the exact cases in which you will be using the functions being tested. However, in this case, they DO represent exactly what I will be doing.
What does this mean? Inklog will no longer use the file system as its main method of data storage.