{"repo":"0xnyn/comet","free":true,"listed":false,"github":"https://github.com/0xnyn/comet","clone":"git clone https://github.com/0xnyn/comet.git","description":"A Vector Store written in Go - Supports hybrid retrieval over BM25, Flat, HNSW, IVF, PQ and IVFPQ Index with Quantization, Metadata Filtering, Reranking, Reciprocal Rank Fusion, Soft Deletes, Index Rebuilds and much much more","language":"Go","stars":131,"topics":["bm25","fts","golang","hnsw","indexing","quantization","search-engine","vector-database","vector-search"],"license":"MIT","category":"databases-storage","readme_excerpt":"Comet A high-performance hybrid vector store written in Go. Comet brings together multiple indexing strategies and search modalities into a unified, hackable package. Hybrid retrieval with reciprocal rank fusion, autocut, pre-filtering, semantic search, full-text search, and multi-KNN searches, and multi-query operations — all in pure Go. Understand search internals from the inside out. Built for hackers, not hyperscalers. Tiny enough to fit in your head. Decent enough to blow it. Choose from: - Flat (exact), HNSW (graph), IVF (clustering), PQ (quantization), or IVFPQ (hybrid) storage backends - Full-Text Search : BM25 ranking algorithm with tokenization and normalization - Metadata Filtering : Fast filtering using Roaring Bitmaps and Bit-Sliced Indexes - Ranking Programmability : Reciprocal Rank Fusion, Fixed size result sets, Threshold based result sets, Dynamic result sets etc. - Hybrid Search : Unified interface combining vector, text, and metadata search Table of Contents - Overview - Features - Installation - Quick Start - Architecture - Core Concepts - API Reference - Examples - Configuration - API Details - Use Cases - Contributing - License Overview Everything you need to understand how vector databases actually work—and build one yourself. What's inside: - 5 Vector Storage Types : Flat, HNSW, IVF, PQ, IVFPQ - 3 Distance Metrics : L2, L2 Squared, Cosine - Full-Text Search : BM25 ranking with Unicode tokenization - Metadata Filtering : Roaring bitmaps + Bit-Sliced Ind","default_branch":null,"files":null,"tree":[],"storefront":"/r/0xnyn","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/0xnyn/comet/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}