chromem-go

Easily use and train state of the art late-interaction retrieval methods (ColBERT) in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.

AI Data Runtime for Agents. Provides serverless Postgres with a multimodal datalake, enabling scalable retrieval and training. Unifies vector storage, dataset management, and streaming data loading for AI agent workflows.

阿里巴巴开源的轻量级高性能进程内向量数据库，采用 C++ 核心实现，支持 Node.js 和 Python 绑定，适用于 RAG、Agent 记忆和向量检索场景。

An interactive visualization tool for large embeddings by Apple. Explore, cross-filter, and search embeddings and metadata to understand and debug embedding models, vector retrieval, and RAG system behavior.