Relational Database Engines on Quantum Platforms

Recent advances in quantum computing have led to the deployment of quantum computers featuring more than 1,000 qubits, with development roadmaps projecting capacities exceeding 100,000 qubits by the next decade. To harness the immense potential of these upcoming systems, it is imperative to concurrently investigate the feasibility of hosting relational database engines on quantum platforms. Notably, there has already been a promising exploration of quantum computing for various DBMS components, including join-order and index-configuration choices. These initial studies have helped gain insight into the fundamental challenges and provided implementation experience. In this tutorial, we present a deep-dive on how quantum computing can be leveraged for database purposes. We begin with an overview of quantum computing fundamentals, followed by a survey of the unique technical challenges that arise on these platforms. Then we consider quantum-based optimization, which can be applied to several DBMS modules, including query optimization, physical schema design, transaction scheduling, resource allocation, etc. We follow up with quantum-based query execution for the basic relational operators, highlighting the architectural mechanisms proposed to work around the restrictions imposed by the probabilistic computational model. Finally, we enumerate the key technical challenges that remain to be addressed to make quantum database engines a reality. In the concluding session, participants will be guided through a hands-on experience of constructing quantum database algorithms, and executing them on both quantum simulators and real quantum hardware.