HelixDB is a graph-vector database that brings structure to vector data, enabling developers to easily build Graph/Hybrid RAG applications. While vector databases have become essential for AI, they fall short when retrieval requires explicit properties or relationships. Existing solutions either bolt vector functionality onto legacy graph databases with poor performance, or force developers to integrate separate systems through middleware, creating overhead and latency bottlenecks.
Built from scratch in Rust, HelixDB leverages world-class expertise in low-level systems programming and algorithms to achieve extreme performance optimizations impossible with existing architectures. This deep technical approach stands in contrast to the LLM-dependent development prevalent in the industry, requiring specialized knowledge in areas where AI tools currently fall short.
The timing is optimal: graph databases are finally gaining recognition after two decades of underutilization, while vector databases have proven their AI value but revealed structural limitations. We emerge as the market awakens to hybrid solutions, positioned early enough to capture the opportunity but not so early as to lack ready adopters.