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arXiv · 2506.09467

ArcNeural: A Multi-Modal Database for the Gen-AI Era

Wu Min·Qiao Yuncong·Yu Tan·Chenghu Yang
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Abstract

ArcNeural introduces a novel multimodal database tailored for the demands of Generative AI and Large Language Models, enabling efficient management of diverse data types such as graphs, vectors, and documents. Its storage-compute separated architecture integrates graph technology, advanced vector indexing, and transaction processing to support real-time analytics and AI-driven applications. Key features include a unified storage layer, adaptive edge collection in MemEngine, and seamless integration of transaction and analytical processing. Experimental evaluations demonstrate ArcNeural's superior performance and scalability compared to state-of-the-art systems. This system bridges structured and unstructured data management, offering a versatile solution for enterprise-grade AI applications. ArcNeural's design addresses the challenges of multimodal data processing, providing a robust framework for intelligent, data-driven solutions in the Gen AI era.

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Wu Min, Qiao Yuncong, Yu Tan, Chenghu Yang. 2025-06-11. ArcNeural: A Multi-Modal Database for the Gen-AI Era. https://arxiv.org/abs/2506.09467

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