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fastfilter_java reviews and mentions
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Bloom Filters – Much, much more than a space efficient hashmap
There are many alternatives to Bloom filters, but some variants of Bloom filters are still competitive. I'm one of the authors of some benchmarks for filters: https://github.com/FastFilter/fastfilter_cpp (this is based on the cuckoo filter benchmark) and https://github.com/FastFilter/fastfilter_java
For static sets (where you construct the filter once and then use it for lookup), blocked Bloom filters are the fastest, for lookup. They do need a bit more space (maybe 10% more than Bloom filters). Also very fast are binary fuse filters (which are new), and xor filters. Cuckoo filters, ribbon filters, and Bloom filters are a bit slower.
For dynamic sets (where you can add and remove entries later), the fastest (again for lookup) are probably "Succinct counting blocked Bloom filter" (no paper yet for this): they are a combination of blocked Bloom filters and counting Bloom filters, so lookup is identical to the blocked Bloom filter. Then cuckoo filters, and counting Bloom filters.
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FastFilter/fastfilter_java is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of fastfilter_java is Java.
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