HDF5 for Python: high level vs low level interfaces. h5py
High-level interfaces are generally going with a performance loss of some sort. After that, whether it is noticeable (worth being investigated) will depend on what you are doing exactly with your code.
Just start with the high-level interface. If the code is overall too slow, start profiling and move the bottlenecks down to the lower-level interface and see if it helps.
I've been working with HDF5 files with C and Matlab, both using the same way for reading from and writing to datasets:

open file with h5f
open dataset with h5d
select space with h5s

and so on...
But now I'm working with Python, and with its h5py library I see that it has two ways to manage HDF5: high-level and low-level interfaces. And with the former it takes less lines of code to get the information from a single variable of the file.
Is there any noticeable loss of performance when using the high-level interface?
For example when dealing with a file with many variables inside, and we must read just one of them.