Also:

* Interfaces to SQL etc. through Python.

* HDF5 support through Pandas. HDF5 is a file format, originally from NASA, for storing large volumes of data, in an efficient yet semantically flexible manner. Within the file there is essentially a complete file system, with symbolic links, etc., and leaf nodes that hold arrays of binary data.

I haven't tried it, but the McKinney book makes it look like an HDF5 file can be represented through a DataFrame object. I can't really picture how this could work if the file were too big to fit into memory -- it would be great if it did, but also a major achievement to do so. This is getting into the functional area of KDB. Does anyone know what is the status of Pandas/NumPy development for large arrays that don't fit into memory?