Quantum computing has recently moved from a theoretical concept to a transformative and increasingly accessible computational paradigm. These developments sparked growing interest in the database community along two complementary directions: applying quantum techniques to improve database tasks, and leveraging DBMS principles to support quantum workloads. This three-hour tutorial provides a bidirectional, practice-oriented treatment of this intersection, covering quantum foundations, optimization algorithms, a systematic survey of Quantum-for-DB and DB-for-Quantum research, and end-to-end system integration with a real DBMS. The tutorial includes hands-on demonstrations using quantum simulators and real quantum hardware. We summarize open challenges and research opportunities for practical real-world deployment.
Quantum computing has recently moved from a theoretical concept to a transformative and increasingly accessible computational paradigm. These developments sparked growing interest in the database community along two complementary directions: applying quantum techniques to improve database tasks, and leveraging DBMS principles to support quantum workloads. This three-hour tutorial provides a bidirectional, practice-oriented treatment of this intersection, covering quantum foundations, optimization algorithms, a systematic survey of Quantum-for-DB and DB-for-Quantum research, and end-to-end system integration with a real DBMS. The tutorial includes hands-on demonstrations using quantum simulators and real quantum hardware. We summarize open challenges and research opportunities for practical real-world deployment.
Quantum computing represents a transformative shift in computational paradigms by leveraging quantum mechanical phenomena such as superposition, entanglement, and quantum interference. Unlike classical computers, which rely on binary logic, quantum systems exploit these principles to solve certain problems more efficiently. This survey presents a comprehensive overview of the field, drawing from extensive literature spanning foundational quantum principles through key quantum algorithms, hardware platforms, and programming tools. The analysis bridges theoretical foundations with practical engineering challenges, examining both current capabilities and fundamental limitations of quantum systems. The paper also explores applications in cryptography, optimization, and quantum simulation, while addressing the ethical implications and long-term prospects of quantum technologies. Distinct from prior surveys, this work provides a unified perspective that connects quantum theory to practical implementation, supporting researchers and students in navigating the evolving landscape of quantum computing.
In the last few years, the field of quantum computing has experienced remarkable progress. The prototypes of quantum computers already exist and have been made available to users through cloud services (e.g., IBM Q experience, Google quantum AI, or Xanadu quantum cloud). While fault-tolerant and large-scale quantum computers are not available yet (and may not be for a long time, if ever), the potential of this new technology is undeniable. Quantum algorithms have the proven ability to either outperform classical approaches for several tasks, or are impossible to be efficiently simulated by classical means under reasonable complexity-theoretic assumptions. Even imperfect current-day technology is speculated to exhibit computational advantages over classical systems. Recent research is using quantum computers to solve machine learning tasks. Meanwhile, the database community has already successfully applied various machine learning algorithms for data management tasks, so combining the fields seems to be a promising endeavour. However, quantum machine learning is a new research field for most database researchers. In this tutorial, we provide a fundamental introduction to quantum computing and quantum machine learning and show the potential benefits and applications for database research. In addition, we demonstrate how to apply quantum machine learning to the join order optimization problem in databases.
Quantum computing has emerged as a transformative tool for future data management. Classical problems in database domains, including query optimization, data integration, and transaction management, have recently been addressed using quantum computing techniques. This tutorial aims to establish the theoretical foundation essential for enhancing methodologies and practical implementations in this line of research. Moreover, this tutorial takes a forward-looking approach by delving into recent strides in quantum internet technologies and the nonlocality theory. We aim to shed light on the uncharted territory of future data systems tailored for the quantum internet.
Quantum computing, grounded in the principles of superposition and entanglement, has emerged as a revolutionary paradigm with the potential to outperform classical systems in specific computational tasks. This paper presents a comprehensive survey of the foundational concepts, algorithmic developments, hardware architectures, and programming ecosystems in quantum computing. We analyze the current progress in key application areas such as cryptography, machine learning, optimization, and quantum chemistry. Furthermore, we review recent advances between 2023 and 2025, including developments in fault-tolerant architectures and quantum error correction. The paper also discusses the significant technical challenges that hinder large-scale practical deployment, including qubit scalability, decoherence, and programming limitations. By synthesizing literature across disciplines, this review aims to provide a holistic understanding of the quantum computing landscape and outline critical directions for future research and integration with classical systems.
This article explores the transformative potential of quantum computing in database systems, focusing on advanced query operations that traditionally challenge conventional architectures. It examines how quantum mechanical phenomena like superposition and entanglement enable unprecedented parallel processing capabilities in database operations. The article investigates key areas including pattern matching, similarity searches, and graph traversal algorithms, where quantum advantages show particular promise. It compares quantum and classical systems, addressing scalability considerations and accuracy challenges in quantum database implementations. The article delves into hybrid quantum-classical architectures and quantum native approaches, examining their respective strengths and limitations. Special attention is given to the challenges and opportunities presented by Noisy Intermediate-Scale Quantum (NISQ) devices, including hardware limitations, algorithm development, and practical integration considerations. The article provides insights into the future directions of quantum databases, emphasizing the importance of developing robust error correction mechanisms and optimizing quantum circuits for practical database operations.
Unlock the future of quantum technology with this comprehensive guide that bridges the gap between complex quantum theory and real-world applications, giving you the practical edge needed to solve the next generation’s toughest scientific and industrial problems. At its core, quantum computing leverages the principles of quantum mechanics to process information in fundamentally different ways from classical computing. As physical limits constrain the continued scaling of classical technologies, quantum computing offers a fundamentally new pathway toward solving complex problems in science, engineering, and industry. This book is a comprehensive guide designed to bridge the gap between theoretical principles and real-world quantum computing applications. It explores quantum information theory, a cornerstone of quantum computing, to explain how information is encoded, manipulated, and measured in a quantum system. Topics such as quantum gates, circuits, and the Bloch sphere representation are covered in detail, offering readers a solid grounding in the mechanics of quantum operations. With a focus on practical implementation, this book is tailored for students, researchers, and professionals seeking to delve into the transformative world of quantum computing, where the boundaries of classical computation are redefined. Readers will find the book: Uses step-by-step guides and hands-on tutorials for building quantum circuits and running algorithms; Explores core algorithms through detailed walkthroughs of quantum algorithms, including Shor’s, Grover’s, and Quantum Fourier Transform; Provides hands-on learning through exercises, coding challenges, and projects to reinforce practical skills. Audience Academics, researchers, quantum software developers and hardware engineers, data scientists, AI specialists, and security experts focused on the study and implementation of quantum systems and processors.