Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search

MySQL-compatible HTAP database with Git for Data, vector search, and fulltext search. Cloud-native, AI-ready

The Kubernetes Operator of Milvus.

Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database​.

A fast Golang CLI for Weaviate and other vector DBs to help view, list, create, delete, and search collections and documents in collections for development, test, and debugging purposes

KektorDB is an in-memory vector database built from scratch in Go. It provides an HNSW-based engine for approximate nearest neighbor search, advanced metadata filtering, and modern access via a REST API and official clients.

A local rag guide with some examples, using PgSql, Ollama and Go

Distributed vector database in Go, WAL crash recovery, and AWS auto-scaling support

query builder of golang, build sql for go framework: sqlx, gorp... build json for Qdrant ....

The Go client for Chroma vector database

Distributed vector search for AI-native applications

The Kubernetes operator for K8ssandra

Go Client for CyborgDB: The Confidential Vector Database

Sorted Data Structure Server - Treds is a Data Structure Server which returns data in sorted order and is the fastest prefix search server. It also persists data on disk.

VM for AI

No fuss multi-index hybrid vector database / search engine

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

Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.

Virtual filesystem implementation in Go with spatial indexing and concurrent operations

Fast, standalone embeddings in Go for text similarity, semantic search, and vector retrieval.