FerresDB

FerresDB is a high-performance vector search engine designed for semantic search, RAG pipelines, and recommendation systems. Key features include: * Sub-millisecond latency for vector queries * Hybrid vector and BM25 text retrieval * REST, gRPC, and WebSocket APIs * Tiered storage management (Hot/Warm/Cold) * High-throughput indexing (50K+ vectors/second) Built entirely in Rust, FerresDB prioritizes speed and reliability with zero garbage collection pauses, ensuring predictable performance. It incorporates HNSW for approximate nearest neighbor search, providing high recall rates for demanding applications. The system includes robust data integrity features like Write-Ahead Log (WAL) and periodic snapshots for crash recovery, alongside an intuitive built-in dashboard for monitoring. FerresDB supports various use cases from transforming user queries into meaning-based results with multiple similarity metrics (Cosine, Euclidean, Dot Product) to grounding large language model responses with relevant context via hybrid search and BM25 fusion. Its multi-protocol API design, including bidirectional streaming gRPC and real-time WebSocket capabilities, makes it adaptable to diverse system architectures. Ideal for engineers and data scientists building search-intensive applications, FerresDB provides enterprise-grade features such as Role-Based Access Control (RBAC) with granular permissions and audit trails. Its zero-downtime re-indexing ensures continuous availability, making it suitable for critical production environments.