HelixDB is a Rust-native database that unifies graph and vector data models to support building retrieval-augmented generation and other AI-powered applications.
HelixDB is a fully native Graph-Vector Database designed to power retrieval-augmented generation (RAG) and AI applications with high performance and low latency. Built in Rust, it combines graph and vector data models in a single engine, allowing developers to store, query, and reason over both structured relationships and unstructured embeddings without stitching together multiple systems. Its primary purpose is to simplify the development of AI-driven applications that require semantic search, knowledge graphs, and complex data relationships.
HelixDB provides native vector indexing and similarity search alongside graph traversal, enabling queries that incorporate both semantic relevance and graph context in one operation. It supports flexible schemas for entities, relationships, and embeddings, making it suitable for evolving AI workloads. The Rust-based implementation focuses on safety and performance, with efficient memory management and concurrency for real-time inference pipelines. By avoiding the overhead of separate graph and vector stores, HelixDB reduces operational complexity and improves query performance for hybrid workloads.
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