Qute: Towards Quantum-Native Database
Muzhi Chen, Xuanhe Zhou, Wei Zhou, Bangrui Xu, Surui Tang, Guoliang Li, Bingsheng He, Yeye He, Yitong Song, Fan Wu
2026-02-17
Summary
This paper introduces Qute, a new type of database that can actually *use* quantum computers to speed up certain tasks, rather than just simulating them on regular computers.
What's the problem?
Traditional databases aren't designed to take advantage of the unique abilities of quantum computers. Existing methods either try to mimic quantum computations on classical computers, which is slow, or awkwardly fit quantum simulations into existing database structures. This means we can't fully unlock the potential speedups quantum computers offer for database operations.
What's the solution?
The researchers built Qute, which works by translating a modified version of SQL (the standard database language) into instructions that a quantum computer can understand. It smartly decides when to use the quantum computer versus a regular computer for different parts of a query, and it uses a special type of indexing that works well with quantum systems. They also figured out a way to store data in a way that minimizes errors caused by the limitations of current quantum computers. They even tested it on a real quantum processor and made the code available for others to use.
Why it matters?
This work is important because it represents a significant step towards building databases that can truly leverage the power of quantum computing. If successful, this could lead to dramatically faster data processing for certain applications, like searching very large datasets or performing complex data analysis, opening up possibilities that are currently impossible with classical computers.
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.