  The FITS (Flexible Image Transport System) data format has been the de facto
data format for astronomy-related data products since its inception in the late
1970s. While the FITS file format is widely supported, it lacks many of the
features of more modern data serialization, such as the Hierarchical Data
Format (HDF5). The HDF5 file format offers considerable advantages over FITS,
such as improved I/O speed and compression, but has yet to gain widespread
adoption within astronomy. One of the major holdbacks is that HDF5 is not well
supported by data reduction software packages and image viewers. Here, we
present a comparison of FITS and HDF5 as a format for storage of astronomy
datasets. We show that the underlying data model of FITS can be ported to HDF5
in a straightforward manner, and that by doing so the advantages of the HDF5
file format can be leveraged immediately. In addition, we present a software
tool, fits2hdf, for converting between FITS and a new `HDFITS' format, where
data are stored in HDF5 in a FITS-like manner. We show that HDFITS allows
faster reading of data (up to 100x of FITS in some use cases), and improved
compression (higher compression ratios and higher throughput). Finally, we show
that by only changing the import lines in Python-based FITS utilities, HDFITS
formatted data can be presented transparently as an in-memory FITS equivalent.
