Epsilla VectorDB

Epsilla is an open-source vector database focused on scalability, high performance and cost-effective vector search. It is designed to connect information retrieval with memory for large language models, so developers building retrieval-augmented generation systems can store embeddings and query them quickly. The core is written in C++ and uses parallel graph traversal techniques for indexing, which the project says is faster than HNSW at comparable precision.

It behaves like a complete database management system, with familiar database, table and field concepts where a vector is just another field type. Features include production-scale similarity search, metadata filtering, hybrid search combining dense and sparse vectors, built-in embedding support for natural-language search, and a cloud-native design with compute and storage separation, serverless operation and multi-tenancy. Integrations cover LangChain and LlamaIndex, and clients are available for Python, JavaScript and Ruby along with a REST API.

You can run the backend in Docker and talk to it from the Python client, or use Epsilla as a Python library without Docker by building the bindings. A managed Epsilla Cloud vector database service is offered and marked experimental. The code is licensed under GPL-3.0.