LlamaIndex

Haystack is a Python library for building vector search and embedding-based retrieval pipelines, integrating ANN indexes without requiring full databases. Key features include support for HNSW, FAISS indexes, quantization options, and multi-language embeddings. Perfect for prototyping RAG systems and embedded AI apps; more flexible than hnswlib, lighter than Milvus for development workflows.

LangChain4j is a Java library providing vector search and embedding capabilities for LLM applications via integrations with ANN indexes like HNSW and FAISS, without needing full vector databases. Features include support for quantization, tool calling, and seamless embedding in JVM environments like Spring Boot and Quarkus. Suited for prototyping RAG agents and embedded apps; lighter and more JVM-native than Milvus, easier integration vs hnswlib.

LEANN is a lightweight RAG-focused library for vector search on embeddings, achieving 97% storage savings via advanced compression and quantization techniques on personal devices. Implemented in Rust/Python, it supports efficient ANN indexing without full DB overhead. Ideal for embedded apps and private prototyping; far lighter than Milvus, more efficient on-device vs hnswlib.

Brinicle is a lightweight C++ library for approximate nearest neighbor (ANN) vector search on embeddings, optimized for low-RAM environments rather than full vector databases. It features efficient graph-based indexing (HNSW-like), supports quantization for further memory reduction, and excels in languages like C++. Ideal for rapid prototyping of ML prototypes and embedded applications; lighter and more memory-efficient than Milvus, with better low-resource performance vs hnswlib.

sqlite-vec is a Rust-based SQLite extension library for vector similarity search using diskANN indexes on embeddings, enabling lightweight ANN without separate databases. Features HNSW-like graphs, quantization support, and hybrid full-text+vector queries in embedded SQLite environments. Perfect for prototyping and on-device apps; extremely lightweight compared to Milvus, more persistent than pure hnswlib.

AnythingLLM is an open-source, self-hosted AI application with integrated vector storage and retrieval for embeddings, enabling RAG and LLM workflows. Key features include built-in RAG, AI agent support, Docker deployment, and free MIT license. Ideal for RAG prototypes and local deployments, providing cost savings and full control compared to managed services like Pinecone.