MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble and HNSW

HyperLogLog with lots of sugar (Sparse, LogLog-Beta bias correction and TailCut space reduction) brought to you by Axiom

JS implementation of probabilistic data structures: Bloom Filter (and its derived), HyperLogLog, Count-Min Sketch, Top-K and MinHash

Fast Web log analyzer using probabilistic data structures

HyperMinHash: Bringing intersections to HyperLogLog

Distributed caching based on StackExchange.Redis and Redis. Includes support for tagging and is cluster-compatible.

Fast and accurate genomic distances using HyperLogLog

C++ Implementations of sketch data structures with SIMD Parallelism, including Python bindings

Sketching Algorithms for Clojure (bloom filter, min-hash, hyper-loglog, count-min sketch)

Dynatrace hash library for Java

Fast HyperLogLog for Python.

Performant implementations of various streaming algorithms, including Count–min sketch, Top k, HyperLogLog, Reservoir sampling.

A probabilistic data structures library for C#

Yet another distributed fault-tolerant key-value database Compatible with Redis written in Golang.

Estimating k-mer coverage histogram of genomics data

Rust's fastest and most accurate cardinality estimators.

Paper about the estimation of cardinalities from HyperLogLog sketches

HyperLogLog cardinality estimation algorithm in go/golang!

The dream accurate approximate set cardinality estimator based on 3-bit HyperLogLog. More accurate than Redis HyperLogLog.

A HyperLogLog implementation in Rust.

SetSketch: Filling the Gap between MinHash and HyperLogLog

Integrates DuckDB with the high-performance Apache DataSketches library. This extension enables users to perform approximate analytics on large-scale datasets using state-of-the-art streaming algorithms, all from within DuckDB.

Probabilistic data structures for OCaml

SQLog - Connecting the dots

go patterns

Rust implementation of probminhash, superminhash and hyperloglog sketching algorithms

A crate for estimating the cardinality of distinct elements in a stream or dataset.

HyperLogLog implementations.

HyperLogLog in golang

A Ruby implementation of the HyperLogLog algorithm for efficient cardinality estimation with minimal memory footprint. Count millions of distinct elements using only kilobytes of memory.