I need to write this up formally, haha. Thanks for the reminder!
Real quick back-of-the-napkin:
SIFT = Safest bet, performant and robust
AKAZE = Can sometimes deal with lower-resolution images better
HAHOG = Incredibly slow, can sometimes match more robust than SIFT
ORB = Can be significantly faster than others, limited to 15k features currently, can handle noisy data
So basically, throw SIFT at everything. If it doesn’t work, maybe try HAHOG if you’ve got the time. After that, come ask us and show us some sample data so we can see if you need to try something different.
AKAZE and ORB are not fully/properly implemented, so they have limitations, though in certain situations they can be worthwhile.