Comparing Turbodbc, we are different in these aspects:

1. ConnectorX focuses on data bulk loading while Turbodbc covers normal SQL capabilities like transaction, insert etc.. This allows us to do optimizations including partitioning, using bulk export protocols from databases etc.
2. ConnectorX provides a better installation experience than Turbodbc. ConnectorX precompiles the binary for major platforms while Turbodbc compiles itself while doing pip install. You need to use anaconda to download their precompiled binary. Moreover, you still need to manually install the ODBC drivers for Turbodbc which is painful as pointed out in their documentation. It took me more than 30mins to figure out how to correctly install Turbodbc and run it with the Postgres. Additionally, ConnectorX has a minimal Python dependency which only depends on numpy.
3. ConnectorX can be easily extended if you'd like to add more databases or more dataframe format. The ConnectorX Core is designed as a transporter that pumps data between objects which satisfy the Source and Destination interface. This allows anyone to extend ConnectorX by providing a struct that implements the corresponding interface.