> For applications that store many items and target moderately low false positive rates, cuckoo filters have lower space overhead than space-optimised Bloom fil

> For applications that store many items and target moderately low false positive rates, cuckoo filters have lower space overhead than space-optimised Bloom filters. Some possible use-cases that depend on approximated set-membership queries would be databases, caches, routers, and storage systems where it is used to decide if a given item is in a (usually large) set, with some small false positive probability. Alternatively, given it is designed to be a viable replacement to Bloom filters, it can also be used to reduce the space required in probabilistic routing tables, speed longest-prefix matching for IP addresses, improve network state management and monitoring, and encode multicast forwarding information in packets, among many other applications. from the original research paper and the repository itself, thank you for asking!