Most client drivers/libs for RDBs have basic type conversions for each language. You don't always need an ORM for this. If you have a ruby or python Time object, the low level db lib generally will convert it to/from the RDB format.
I've used both simple and complex mapping methods. At the moment, I'm using mongodb with very simple first class object wrappers around the hash/dict. This is appropriate for this new app.
For an app I already have in production, I use postgresql and ruby's datamapper. This limits me to knowing that adding some features requires more work so those features keep getting pushed off the plate. The reason I use postgres for this app is because my users expect RDB ACID properties. For the new app I'm working on, not so much.
Didn't know that. If that's correct, then the low-level db lib is an ORM in Python. In which case SQLObject/SQLAlchemy probably just harnesses those features and adds some additional cream on top.
An ORM adds stuff on top of the driver. General these frameworks provide relationship management, connection pooling, caching, and config management.
Object-relational mapping (ORM, O/RM, and O/R mapping) in computer software is a programming technique for converting data between incompatible type systems in relational databases and object-oriented programming languages.
If you really want to know what's in various lower level drivers, as opposed to ORM frameworks (which vary quite a bit themselves), just go crack open some code and look at the APIs for yourself. You can go pretty far back to MS ODBC libs or even vendor dependent Oracle libs from mid to late 80s and see they were used quite effectively on their own for many years. JDBC was fairly straightforward derived from these predecessors.
Did you consider using SQLObject or SQLAlchemy? If so, I'd be curious to know why you decided against using them?