Orama is a lightweight search engine that supports vector and hybrid search functionalities, suitable for browser, server, or edge environments.

ClickHouse is a columnar OLAP database with vector indexes (ANN via AMM, brute-force), supporting SQL queries over vectors + structured data at petabyte scale. Excels in aggregations with vectors. For analytics workloads with embeddings; faster ingestion than Postgres pgvector for big data.

LlamaIndex is a Python data framework library for vector search and embedding retrieval, integrating various ANN indexes like HNSW and FAISS without full database dependencies. Supports quantization, multi-modal embeddings, and advanced query engines in Python/Rust backends. Great for prototyping LLM apps and embedded RAG; more developer-friendly and lighter than Milvus, composable vs hnswlib.

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.

Valkey is an open-source in-memory key-value data store that supports vector search operations, making it useful for AI and machine learning vector database workloads. It is also a specialized open-source vector database designed for efficient management and retrieval of high-dimensional vector data, offering advanced APIs and optimized storage for AI workloads.

A distributed vector database designed for scalable and efficient vector similarity search. It is purpose-built for handling large-scale vector data and search workloads.