I think jump-based consistent hashing also requires less memory, O(1), than rendezvous hashing.
From my limited perspective and the paper linked in the article it sounds like consistent hashing is best for numbered sharding (disk storage systems and databases) and rendezvous hashing is best for arbitrarily distributed storage where nodes can't be consecutively numbered.
My best attempt at explaining jump consistent hashing is that it's possible to determine how likely a given key will be to move to a nearby bucket (small hash values make it less likely, large hash values make it more likely) and use that likelihood to choose a next bucket candidate for each key. About half of keys are likely to move from 1 bucket to 2, but only a third are likely to move from 2 buckets to 3, etc. and in general 1/n of keys are likely to move to bucket n.
From my limited perspective and the paper linked in the article it sounds like consistent hashing is best for numbered sharding (disk storage systems and databases) and rendezvous hashing is best for arbitrarily distributed storage where nodes can't be consecutively numbered.
My best attempt at explaining jump consistent hashing is that it's possible to determine how likely a given key will be to move to a nearby bucket (small hash values make it less likely, large hash values make it more likely) and use that likelihood to choose a next bucket candidate for each key. About half of keys are likely to move from 1 bucket to 2, but only a third are likely to move from 2 buckets to 3, etc. and in general 1/n of keys are likely to move to bucket n.