Is there an analysis speed or memory usage advantage to using HDF5 for large array storage (instead of flat binary files)?

Is there an analysis speed or memory usage advantage to using HDF5 for large array storage (instead of flat binary files)?

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HDF5 taking more space than CSV?

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Improve pandas (PyTables?) HDF5 table write performance

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Convert large csv to hdf5

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Missing optional dependency 'tables'. In pandas to_hdf

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pd.read_hdf throws 'cannot set WRITABLE flag to True of this array'

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Python, PyTables, Java - tying all together

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Iteratively writing to HDF5 Stores in Pandas

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Storing numpy sparse matrix in HDF5 (PyTables)

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Pandas "Group By" Query on Large Data in HDFStore?

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install HDF5 and pytables in ubuntu

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Python: how to store a numpy multidimensional array in PyTables?

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How to get faster code than numpy.dot for matrix multiplication?

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Saving dictionaries to file (numpy and Python 2/3 friendly)

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python