Probabilistic data structures for processing continuous, unbounded streams.
-
Updated
Mar 15, 2021 - Go
Probabilistic data structures for processing continuous, unbounded streams.
A fast bloom filter implemented by Rust for Python! 10x faster than pybloom!
A probabilistic data structures library for C#
A class library implementing probabilistic data structures in .NET
A counting bloom filter with probabilistic deletion capabilities also allowing a risky deletion which may lead to false negatives if not carefully used.
Add a description, image, and links to the counting-bloom-filters topic page so that developers can more easily learn about it.
To associate your repository with the counting-bloom-filters topic, visit your repo's landing page and select "manage topics."