xor_singleheader VS fastfilter_java

Yes. Some variants of ribbon filters are very fast, and other variants (which are a bit slower thought) need very little space: only a few percent more than the theoretical lower bound.

For static sets, ribbon filters and binary fuse filters (e.g. here: https://github.com/FastFilter/xor_singleheader) are very competitive. Both are based on recent (2019 and newer) theoretical work from Stefan Walzer, e.g. this one https://arxiv.org/pdf/1907.04749.pdf

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.