No doubt that much longer :) But the important points to take away are: 1) You can store more compressed data by using the same storage capacities. 2) If data

No doubt that much longer :) But the important points to take away are: 1) You can store more compressed data by using the same storage capacities. 2) If data can be compressed, the I/O effort will be less 3) If the compressor is fast enough, you may end saving I/O time As for 2), Blosc can be pretty fast as can be seen in: http://blosc.pytables.org/trac/wiki/SyntheticBenchmarks http://blosc.pytables.org/trac/wiki/SyntheticBenchmarks so, in general, will speed up I/O for compressible data (even if that data is in-memory).