Qute: Towards Quantum-Native Database
Abstract
This paper envisions a quantum database (Qute) that treats quantum computation as a first-class execution option. Unlike prior simulation-based methods that either run quantum algorithms on classical machines or adapt existing databases for quantum simulation, Qute instead (i) compiles an extended form of SQL into gate-efficient quantum circuits, (ii) employs a hybrid optimizer to dynamically select between quantum and classical execution plans, (iii) introduces selective quantum indexing, and (iv) designs fidelity-preserving storage to mitigate current qubit constraints. We also present a three-stage evolution roadmap toward quantum-native database. Finally, by deploying Qute on a real quantum processor (origin_wukong), we show that it outperforms a classical baseline at scale, and we release an open-source prototype at https://github.com/weAIDB/Qute.
Keywords
Cite
@article{arxiv.2602.14699,
title = {Qute: Towards Quantum-Native Database},
author = {Muzhi Chen and Xuanhe Zhou and Wei Zhou and Bangrui Xu and Surui Tang and Guoliang Li and Bingsheng He and Yeye He and Yitong Song and Fan Wu},
journal= {arXiv preprint arXiv:2602.14699},
year = {2026}
}
Comments
Please refer our open-source prototype at: https://github.com/weAIDB/Qute