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  • For compute intensive jobs (e.g. detectors the require many corrections) MPIDataSource can be run in parallel, dramatically speeding up computing
  • Users have critical control of what data goes in to the hdf5 file.  In particular, the old translator often outputs raw data arrays, while the user typically wants calibrated/corrected images
  • The datasets in MPIDataSource are guaranteed to be time-aligned across datasets
  • Users can also store miscellaneous user-defined values in the hdf5 (e.g. integrated images)
  • HDF5 dataset format HDF5 schema from MPIDataSource is much simpler
  • The old translator is very complex, and no longer actively supported (data types later than 2017 are not included, the year the author of the code left SLAC)