DeepFace previously relied on filesystem-based datasets and pickle caches for face search, which made it stateful and hard to expose via APIs.

We introduced register and search functions that store embeddings in a backend DB (Postgres, Mongo, Weaviate, Neo4j).

This makes face recognition stateless, horizontally scalable, and suitable for API use.

For Postgres and Mongo, FAISS is used for ANN search; Weaviate and Neo4j handle vector indexing natively.

Additional databases and vector stores can be added over time.