Over the years, I've found myself building hacky solutions to serve and manage my embeddings. I’m excited to share Embeddinghub, an open-source vector database for ML embeddings. It is built with four goals in mind:

Store embeddings durably and with high availability

Allow for approximate nearest neighbor operations

Enable other operations like partitioning, sub-indices, and averaging

Manage versioning, access control, and rollbacks painlessly

It's still in the early stages, and before we committed more dev time to it we wanted to get your feedback. Let us know what you think and what you'd like to see!

Repo: https://github.com/featureform/embeddinghub

Docs: https://docs.featureform.com/

What's an Embedding? The Definitive Guide to Embeddings: https://www.featureform.com/post/the-definitive-guide-to-emb...