numpy: difference between NaN and masked array

In numpy there are two ways to mark missing values: I can either use a NaN or a masked array. I understand that using NaNs is (potentially) faster while masked array offers more functionality (which?).

I guess my question is if/ when should I use one over the other? What is the use case of np.NaN in a regular array vs. a masked array?

I am sure the answer must be out there but I could not find it...