To facilitate this process, diagramming your basic metaphors and the way users interact with your system is very useful. 'Field Definition' components and the FileMaker data however, can be converted to PostgreSQL tables fairly easily. In order to convert a database from FileMaker to PostgreSQL, the most common method will be to manually create each table, and make decisions about field type definitions. There are several different data types in FileMaker text, number, date, time, container, calculation, summary and global.ĭate and time definitions have their obvious counterparts in PostgreSQL.

Text is just like 'text' in PostgreSQL, basically unlimited in size. There are no equivalents in FileMaker to char and varchar data types. If you have small text fields, for things like Zip Codes, Phone numbers and the like, you might want to use the varchar or char data types instead of text. #MIGRATING FROM FILEMAKER PRO 10 TO 13 MAC ZIP# In FileMaker, the number type does not have a precision - it can be an integer, or a float. What distinguishes them in a FileMaker database is the formatting of the output, not the storing of the number - the number is stored as floating point. So when porting to PostgreSQL, determine what fields can be integers and what fields should be floating point. The other data types provide for very specific problems in terms of converting the database from FileMaker to PostgreSQL. Calculation and Summary field types in FileMaker will have to be ported either by using functions within PostgreSQL, or by including these calculations in the programming interaction between PostgreSQL and the front-end.ĭata export from FileMaker and import into PostgreSQLĮxporting data from FileMaker is quite easy. There are a number of formats available, and many provide important options that might make life a little easier. #MIGRATING FROM FILEMAKER PRO 10 TO 13 MAC ZIP#.

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