[1] Unlike most other key-value stores, Judy arrays use no hashing, leverage compression on their keys (which may be integers or strings), and can efficiently represent sparse data; that is, they may have large ranges of unassigned indices without greatly increasing memory usage or processing time.
They are designed to remain efficient even on structures with sizes in the peta-element range, with performance scaling on the order of O(log n).
Judy arrays are designed to minimize the number of expensive cache-line fills from RAM, and so the algorithm contains much complex logic to avoid cache misses as often as possible.
On data sets that are sequential or nearly sequential, Judy arrays can even outperform hash tables, since, unlike hash tables, the internal tree structure of Judy arrays maintains the ordering of the keys.
[5] In addition, Judy arrays are optimized for machines with 64 byte cache lines, making them essentially unportable without a significant rewrite.