pgEdge

Embeddable SQL OLAP engine with VSS extension for low-latency HNSW vector search on local files, ideal for edge AI prototyping and analytics. SQL-first approach for on-device vector ops vs cloud vector DBs like Qdrant.

Lightweight embedded vector store for low-latency on-device vector operations in prototyping AI apps, using HNSW for fast ANN search with built-in embeddings and metadata filtering. Enables quick local RAG on edge devices; simpler and lower-latency than cloud Qdrant for developer workflows.

Embedded NoSQL database enabling low-latency on-device vector search for offline GenAI on mobile/IoT/browsers via ANN indexing. ACID-compliant with sync replication for edge RAG; more mobile-focused and offline-capable than cloud Qdrant.

Lightweight Node.js library for low-latency on-device vector similarity search using HNSW and BM25 hybrid, with CRUD, metadata filtering, and persistence for edge RAG pipelines. Enables real-time semantic search without servers; more lightweight than cloud Qdrant.

Minimal Rust library for fast on-device cosine similarity search with Rayon parallelism and embedded persistence, ideal for low-latency prototyping on edge hardware. Supports quick inserts/queries for real-time AI; lighter than full DBs like Qdrant edge.

Resource-efficient on-device vector database with sync for mobile/IoT/embedded, enabling low-latency offline AI vector ops without cloud. Supports edge-first apps; more efficient than server-based Qdrant.