|The following people and organisations have donated time money and equipment towards making unixODBC the complete ODBC solution for non windows platforms - Nick Gorham
You may want a commercial solution to your ODBC desires... here is a good start. EasySoft has been very helpfull in the development of unixODBC so I strongly urge you to consider checking out their products.
These folks use unixODBC but even more importantly... they have been a very big supporter of unixODBC by providing some of their programming time and network resources for unixODBC.
I got involved
in ODBC for Linux while looking for a data access solution for some commercial
application development. I naturally looked for an ODBC solution having
used it extensively on projects targeted towards MS Windows platforms.
I spent about three days browsing the web, downloading stuff, and generally
trying to find a standard solution that I could promote as the basis for
our future development (Dec.98). I found some good starts but nothing even
remotely close to a complete, standard, and free solution that I could
possibly hope to ever expect on the majority of Linux installations. This
prompted me to start the cbdODBC Project which turned into LinuxODBC and
finally into unixODBC. Please check out the unixODBC
home page for where things are today or jump to some of these sites
which I have uncovered in my travels. - Peter Harvey
Another commercial provider of data access technology.
This is a very well written, JDBC-like, class wrapper for ODBC. It can used with unixODBC.
OTL provides an API similar to ordinary C++ streams. OTL is tightly integrated with STL via STL-compliant stream iterators
The goal of this library is to make ODBC recordsets look just like an STL container.
Large list of ODBC drivers, though many are Windows only.
Python ODBC interface.
SWI-Prolog uses unixODBC to provide database connectivity on Unix.
Ch ODBC toolkit is Ch binding to ODBC
Turbodbc brings turbocharged database access for data scientists to Python. It uses buffered I/O for efficiency and comes with built-in NumPy support.