dBase to MySQL

I need a small tool (best would be commandline) that synchronizes a dBase to a MySQL database. As a demonstration you can have a look at [login to view URL] I don't need bidirectional synchronization yet. The tool should be for Suse Linux. Most important is that the tool is fast as it should run approx once a minute, perfect would be a tool that syncs in realtime. Datasource is a bunch of .dbf files demo data will be delivered. Last info: the dbf files will be stored on an networkdrive that is mounted locally (I don't think that this matters). As there are some FAQ: 1. attached are now some sample dbf files as one zip. 2. the data in mysql will be one table per dbf file. 3. naming of the tables will be PREFIX + dbf name 4. columns in the mysql have to be created by the tool according to the dbf data (so 1:1) The dbf files are ANSI character coded the tool has to handle that (german special chars as äöü...) The dbf files will be between 30 to 1000 entries perhaps sometimes even more. The names of the dbf files can change so the solution will be that your tool requests a parameter filename/s and will synchronize the given files to mysql. Again sumarized There will be a buch of dbf files that exists This files are synchronized to mysql once to have a start The dbf files will change frequently The changes have to be reflected in the mysql database as fast as possible I have to learn that I should describe my projects in more detail from the beginning... There is no timestamp in the dbf files so the tool will have to find out what has been changed between the last synchronization and now by it's own. I think this could be reached by different ways. 1. keeping a local copy of the syncronized dbf files and comparing this to the original once 2. by some kind of hashing 3. by relying on the "last changed date" on filesystem level In all cases the steps would be 1. synchronize dbfs with mysql 2. store whatever needed to find the differences 3. check which dbf files are changed 4. find the updated records what is probably the most difficult step 5. write the changes to the mysql and restart at step 2 There are about 21 dbf files that have to be synchronized but I assume that only about 5 files are really changed between each run.