PyTables is built on top of the HDF5 library, using the Python language and the Numpy package (it also supports NumArray and Numeric right out of the box). It features an object-oriented interface that, combined with C extensions for the peformance-critical parts of the code (generated using Pyrex), makes it a fast, yet extremely easy to use tool for interactively saving and retrieving very large amounts of data. One important feature of PyTables is that it optimizes memory and disk resources so that data takes much less space (a factor between 3 and 5, and more if the data is compressible) than other solutions such as relational or object oriented databases.

Home Page: http://www.pytables.org
How To Use: http://www.pytables.org/moin/HowToUse
Bug Reports: http://www.pytables.org/trac/
Mailing List: https://lists.sourceforge.net/lists/listinfo/pytables-users
Source Forge Page: http://sourceforge.net/projects/pytables

 Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them).

 The tables are both enlargeable and compressible.

 I/O is buffered, so you can get very fast I/O, specially with large tables.

 Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well.

 It supports all the NumPy, numarray and Numeric packages.