Accelerating Relational Database Management Systems via Quantum Computing

Project Coordinator: Prof. Dr. Sven Groppe

Research Associate: Tobias Winker

Research Associate: Umut Çalıkyılmaz  

Research Associate: Nitin Nayak

Research Associate: Benjamin Warnke  

Motivation

Almost all applications in the digital world rely on fast approaches to data management. Relational database management systems (RDBMS), databases consisting of two-dimensional tables, are the most widespread type of database management system. Certain time-consuming tasks can be accelerated through the application of quantum computing, so lower latencies and faster execution promise a smooth experience for users.

Goals and Procedure

Two problems are examined in more detail in the project. On the one hand, the translation of RDBMS queries into expressions of relational algebra. Typically, there is a large number of equivalent expressions, from which the expression estimated to be optimal must be selected.
On the other hand, transactions are a fundamental concept of databases: A transaction is a sequence of operations in the form of read and write requests that are carried out by a single user or application program. Transaction schedule tuning determines the optimal order of parallel execution of transactions for best performance.

Innovation and Prospects

Both problems, the optimization of queries as well as transaction plans, can be reduced to the application of basic mathematical optimization approaches and accelerated by quantum computers. Classic routines are replaced by their quantum computing counterparts, which promise quadratic accelerations in many cases.

Project Partners

Quantum Brilliance GmbH: https://quantumbrilliance.com/ 

Link to Project Details

https://www.quantentechnologien.de/forschung/foerderung/anwendungsnetzwerk-fuer-das-quantencomputing/qc4db.html  

Activities

Publications

2024

  • Maja Franz, Tobias Winker, Sven Groppe, Wolfgang Mauerer: Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisation
    in: arXiv, 2024, Vol.2405.07770
    Website BibTeX
  • Nitin Nayak, Tobias Winker, Umut Çalıkyılmaz, Sven Groppe, Jinghua Groppe: Quantum Join Ordering by Splitting the Search Space of QUBO Problems
    in: Datenbank-Spektrum, 2024, Vol.24, (1), p.21-32
    Website BibTeX
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2023

  • Le Gruenwald, Tobias Winker, Umut Çalıkyılmaz, Jinghua Groppe, Sven Groppe: Index Tuning with Machine Learning on Quantum Computers for Large-Scale Database Applications
    in: Joint Proceedings of Workshops at the 49th International Conference on Very Large Data Bases (VLDB 2023) - International Workshop on Quantum Data Science and Management (QDSM 23), Vancouver, Canada, 2023
    Website BibTeX
  • Valter Uotila, Sven Groppe, Le Gruenwald, Jiaheng Lu, Wolfgang Mauerer: Preface QDSM
    in: Joint Proceedings of Workshops at the 49th International Conference on Very Large Data Bases (VLDB 2023) - International Workshop on Quantum Data Science and Management (QDSM 23), Vancouver, Canada, 2023
    Website BibTeX
  • Umut Çalıkyılmaz, Sven Groppe, Jinghua Groppe, Tobias Winker, Stefan Prestel, Farida Shagieva, Daanish Arya, Florian Preis, Le Gruenwald: Opportunities for Quantum Acceleration of Databases: Optimization of Queries and Transaction Schedules
    in: Proc. VLDB Endow., 2023, Vol.16, (9), p.2344-2353
    Website BibTeX
  • Tobias Winker, Sven Groppe, Valter Uotila, Zhengtong Yan, Jiaheng Lu, Maja Franz, Wolfgang Mauerer: Quantum Machine Learning: Foundation, New Techniques, and Opportunities for Database Research
    in: Proceedings of ACM SIGMOD/PODS International Conference on Management of Data (SIGMOD), 2023
    Website BibTeX
  • Tobias Winker, Umut Çalıkyılmaz, Le Gruenwald, Sven Groppe: Quantum Machine Learning for Join Order Optimization using Variational Quantum Circuits
    in: Proceedings of the International Workshop on Big Data in Emergent Distributed Environments (BiDEDE), Seattle, WA, USA, 2023
    Website BibTeX
  • Nitin Nayak, Jan Rehfeld, Tobias Winker, Benjamin Warnke, Umut Çalıkyılmaz, Sven Groppe: Constructing Optimal Bushy Join Trees by Solving QUBO Problems on Quantum Hardware and Simulators
    in: Proceedings of the International Workshop on Big Data in Emergent Distributed Environments (BiDEDE), Seattle, WA, USA, 2023
    Website BibTeX
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2022

  • Sven Groppe, Jinghua Groppe, Umut Çalıkyılmaz, Tobias Winker, Le Gruenwald: Quantum Data Management and Quantum Machine Learning for Data Management: State-of-the-Art and Open Challenges
    in: Proceedings of the EAI International Conference on Intelligent Systems and Machine Learning (EAI ICISML 2022), 2022
    BibTeX
nach oben