boomfilters

Includes implementations for Stable Bloom Filters, Scalable Bloom Filters, HyperLogLog, and more, covering most probabilistic data needs in stream processing as detailed in the README.

Designed for unbounded data streams with configurable memory usage, such as Stable Bloom Filters evicting stale data to maintain stable false-positive rates.

Allows setting parameters like false-positive rates and error bounds, enabling developers to balance accuracy, memory, and performance based on specific use cases.

Provides clear usage examples, serialization support for structures like HyperLogLog, and references to academic papers, facilitating real-world adoption.