Cuckoo Filter: Practically better than Bloom filter implemented in Go
Cuckoo Filter: Practically better than bloom filter - vedhavyas/cuckoo-filter
Cuckoo Filter: Practically better than Bloom filter implemented in Go launched on October 26, 2017 with 16 votes, #917 of 3,169 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 8 years on.
In plain words
Cuckoo Filter is a Go implementation of a probabilistic data structure used for membership testing. It determines whether an item exists in a set with minimal memory overhead, similar to a Bloom filter but with practical performance improvements. Developers and engineers working with large datasets or systems requiring efficient duplicate detection or set membership queries would find this tool useful. The implementation prioritizes practical performance benefits over traditional Bloom filter approaches.
written from the facts on this page · September 2026
Does a similar job
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Cuckoo Filter Implementation in Go, Better Than Bloom Filters2016 · github.com · ▲181Cuckoo Filter implementation in Go, better than Bloom Filters (unmaintained) - irfansharif/cfilter
Cuckoo Filter in Ruby2017 · github.com · ▲74Pure Ruby Cuckoo Filter Implementation. Contribute to pawandubey/cuckoo_filter development by creating an account on GitHub.
GPU Cuckoo Filter – faster queries than Blocked Bloom, with deletionJan 2026 · github.com · ▲32High-Performance GPU Cuckoo Filter. Contribute to tdortman/Cuckoo-GPU development by creating an account on GitHub.
BloomSearch – Keyword search with hierarchical Bloom filters2025 · github.com · ▲66Hey HN! I got nerd-sniped by Bloom Filters this weekend, specifically for searching datasets with high "cardinality" (number of unique items). They're an _amazing_ data structure that, at a fixed size, tracks potential set membership. That means unlike normal b-tree indexes, they don't grow with the number of unique items in the dataset. This makes them great for "needle in a haystack" search (logs, document) as implementations like VictoriaMetrics and Bing's BitFunnel show. I've used them in the past, but they've never been center-stage in my projects. I wanted high cardinality keyword…
- BFBloom Filter2017 · sacert.github.io · ▲65
BoomFilters – Probabilistic data structures for processing streams2015 · github.com · ▲70Probabilistic data structures for processing continuous, unbounded streams. - tylertreat/BoomFilters
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