# Embedded & Edge Vector Databases

> Browse 15 items in Embedded & Edge Vector Databases.

## Items

- [DuckDB](https://vectordb.ever.works/th/items/duckdb) — 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.
- [Chroma Local Embedding Database](https://vectordb.ever.works/th/items/chroma-local-embedding-db) — 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.
- [Couchbase Lite Vector](https://vectordb.ever.works/th/items/couchbase-lite-vector) — 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.
- [embedded-vector-db](https://vectordb.ever.works/th/items/embedded-vector-db) — 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.
- [nano-vectordb-rs](https://vectordb.ever.works/th/items/nano-vectordb-rs) — 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.
- [ObjectBox Vector](https://vectordb.ever.works/th/items/objectbox-vector) — 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.
- [pgEdge](https://vectordb.ever.works/th/items/pgedge) — Distributed PostgreSQL extension for edge deployments enabling low-latency vector processing closer to users across multi-region nodes with consistency. Supports on-device vector ops in edge environments vs centralized cloud DBs like Qdrant.
- [RuVector](https://vectordb.ever.works/th/items/ruvector) — Self-optimizing on-device vector database with HNSW, graph RAG, and WASM deployment for low-latency edge AI ops across browsers/IoT/mobile. Supports real-time self-learning retrieval; lighter and offline vs cloud Qdrant.
- [ruvector-core](https://vectordb.ever.works/th/items/ruvector-core) — Rust core for high-performance on-device HNSW vector search with SIMD and compression, achieving low-latency multi-threaded queries for edge AI RAG. Up to 3,597 QPS; optimized for real-time vs cloud alternatives.
- [rvf-launch](https://vectordb.ever.works/th/items/rvf-launch) — QEMU microVM launcher for low-latency RVF cognitive containers in RuVector stack, enabling secure on-device vector processing for edge AI environments.
- [rvLite](https://vectordb.ever.works/th/items/rvlite) — Compact 2MB standalone database for low-latency vector search on IoT/mobile/embedded, no server needed for on-device real-time AI ops.
- [Sonic](https://vectordb.ever.works/th/items/sonic) — Fast in-memory backend with HNSW vector support for low-latency on-device hybrid full-text + vector search, ideal for edge performance-critical apps. Sub-ms ingest/retrieval; lightweight alternative to cloud Qdrant.
- [tinyvector](https://vectordb.ever.works/th/items/tinyvector-m1guelpf) — Pure Rust embedding database as lightweight Axum server for low-latency on-device vector search scaling to 100M+ vectors in memory. High accuracy/speed for edge RAG; simpler than Qdrant edge.
- [Victor](https://vectordb.ever.works/th/items/victor) — Web-optimized Rust vector DB for low-latency on-device storage/search via WASM, with efficient formats and PCA compression for browsers/edge. Supports JS/Rust APIs; compact vs cloud Qdrant.
- [VortexDB](https://vectordb.ever.works/th/items/vortexdb) — Rust-built vector DB with pluggable HNSW/KD-Tree/Flat indexers for low-latency on-device similarity search, HTTP/gRPC/TUI clients, RocksDB persistence. Suited for edge AI; modular vs monolithic Qdrant.

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_Canonical page: https://vectordb.ever.works/th/categories/embedded-edge-vector-databases_