HyperLogLog Distinct Value Estimator
HyperLogLog Distinct Value Estimator with an alternative implementation to murmurhash 128bit based on murmurhash-native instead of murmurhashv3
JS implementation of probabilistic data structures: Bloom Filter (and its derived), HyperLogLog, Count-Min Sketch, Top-K and MinHash
hyperloglog support for mongo (16kb per counter)
JS implementation of probabilistic data structures: Bloom Filter (and its derived), HyperLogLog, Count-Min Sketch, Top-K and MinHash
a hyperloglog implementation
HyperLogLog using a 32-bit murmurhash3 for node and browser
Stream-based HyperLogLog implementation
A native HyperLogLog lib.
HyperLogLog Distinct Value Estimator
Count distinct values/cardinalities using HyperLogLog algrithm.
TypeScript implementation of HyperLogLog algorithm
Set cardinality estimates using HyperLogLog implementation
NIP-45 HyperLogLog implementation in Javascript
A Redis backed HyperLogLog implementation for node.js.
JS implementation of probabilistic data structures: Bloom Filter (and its derived), HyperLogLog, Count-Min Sketch, Top-K and MinHash
Cube.js pre-aggregation storage layer.
Native (plain C and C++) HLL implementation for node.js
Efficiently estimate the cardinality of a set in Typescript and Javascript
High-performance probabilistic data structures for Node.js - 41 algorithms with 28-75% better space efficiency than classic algorithms
Provides implementations of sketch algorithms for real-time counting of stream data. Useful for real-time web analytics and other streaming or big data scenarios.
probabilistic data structure in js
Probabilistic data structures for TypeScript/Node.js via WebAssembly
HLLD client
Hyperloglog implementation in Rust
A Redis-compatible HyperLogLog service with pluggable storage backends
A Rust implementation of HyperLogLog trying to be parsimonious with memory.
Collection of stream analytics algorithms: cardinality, quantiles, frequency, sampling, and more
submillisecond.com cookbook recipe - data-structures: subms-hyperloglog. Distinct-count cardinality estimator. ~1% standard error at ~16 KB.
thread-safe hyperloglog, with atomics
Estimate the cardinality of distinct elements in a stream or dataset with no unsafe code
A crate for estimating the cardinality of distinct elements in a stream or dataset.
High-performance HyperLogLog with bias correction and full concurrency support.
Genome/Metagenome sketching via, HyperLogLog, HyperMinHash and UltraLogLog
A simple HyperLogLog implementation in rust
Probabilistic data structure library: Bloom filters, Cuckoo filters, Count-Min Sketch, HyperLogLog, MinHash, and Top-K. Tunable false-positive rates, serializable state, merge support, and streaming-safe updates.
An efficient implementation of the HyperLogLog cardinality estimator
An implementation of the HyperLogLog set cardinality estimation algorithm in Ruby using Redis as a back-end
HyperLogLog implementation in pure Ruby
HyperLogLog for Rails and Postgres
A library to add hyperloglog functionality to lambda store in ruby
Hyll provides a robust implementation of the HyperLogLog algorithm, enabling highly accurate cardinality estimation (counting unique items) with minimal memory footprint. Perfect for analytics, databases, and stream processing where tracking distinct elements in large datasets is required. This implementation offers configurable precision and serialization support.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.