QC4DB: Accelerating Relational Database Management Systems via Quantum Computing

Funded by:

  • BMBF

Laufzeit:

  • 01.01.2022 - 31.12.2024 / 30.06.2025

Project Coordinator: 

Research Associates:

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

Link to Project Details at National Funding Body

QC4DB - Quantentechnologien

Activities

Publications

2024

Maja Franz, Tobias Winker, Sven Groppe, and Wolfgang Mauerer,
Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisation, arXiv , vol. 2405.07770, 2024.
File: arXiv.2405.07770
Nitin Nayak, Tobias Winker, Umut Çalıkyılmaz, Sven Groppe, and Jinghua Groppe,
Quantum Join Ordering by Splitting the Search Space of QUBO Problems, Datenbank-Spektrum , vol. 24, no. 1, pp. 21-32, 2024.
File: s13222-024-00468-3
Benjamin Warnke, Kevin Martens, Tobias Winker, Sven Groppe, Jinghua Groppe, Prasad Adhiyaman, Sruthi Srinivasan, and Shridevi Krishnakumar,
ReJOOSp: Reinforcement Learning for Join Order Optimization in SPARQL, Big Data and Cognitive Computing (BDCC) , vol. 8, no. 7, 2024.
File: bdcc8070071

2023

Nitin Nayak, Jan Rehfeld, Tobias Winker, Benjamin Warnke, Umut Çalıkyılmaz, and 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.
File: 3579142.3594298
Bibtex: BibTeX
@inproceedings{Nayak2023QUBO_JOO,
	title = {Constructing Optimal Bushy Join Trees by Solving QUBO Problems on Quantum Hardware and Simulators},
	author = {Nitin Nayak and Jan Rehfeld and Tobias Winker and Benjamin Warnke and Umut Çalıkyılmaz and Sven Groppe},
	booktitle = {Proceedings of the International Workshop on Big Data in Emergent Distributed Environments (BiDEDE), Seattle, WA, USA},
	year = {2023},
	url = {https://doi.org/10.1145/3579142.3594298}
}
Le Gruenwald, Tobias Winker, Umut Çalıkyılmaz, Jinghua Groppe, and 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 , CEUR-WS.org, 2023.
File: QDSM5.pdf
Bibtex: BibTeX
@inproceedings{Gruenwald2023IndexTuning,
	title = {Index Tuning with Machine Learning on Quantum Computers for Large-Scale Database Applications},
	author = {Le Gruenwald and Tobias Winker and Umut Çalıkyılmaz and Jinghua Groppe and Sven Groppe},
	booktitle = {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},
	year = {2023},
	url = {https://ceur-ws.org/Vol-3462/QDSM5.pdf}
}
Umut Çalıkyılmaz, Sven Groppe, Jinghua Groppe, Tobias Winker, Stefan Prestel, Farida Shagieva, Daanish Arya, Florian Preis, and Le Gruenwald,
Opportunities for Quantum Acceleration of Databases: Optimization of Queries and Transaction Schedules, Proc. VLDB Endow. , vol. 16, no. 9, pp. 2344--2353, 2023.
File: 3598581.3598603
Bibtex: BibTeX
@article{Calıkyilmaz2023QC_QO_TSO,
	title = {Opportunities for Quantum Acceleration of Databases: Optimization of Queries and Transaction Schedules},
	author = {Umut Çalıkyılmaz and Sven Groppe and Jinghua Groppe and Tobias Winker and Stefan Prestel and Farida Shagieva and Daanish Arya and Florian Preis and Le Gruenwald},
	journal = {Proc. {VLDB} Endow.},
	volume = {16},
	number = {9},
	pages = {2344--2353},
	year = {2023},
	url = {https://doi.org/10.14778/3598581.3598603}
}
Valter Uotila, Sven Groppe, Le Gruenwald, Jiaheng Lu, and 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 , CEUR-WS.org, 2023.
File: QDSM1.pdf
Bibtex: BibTeX
@inproceedings{Uotila2023QDSM,
	title = {Preface {QDSM}},
	author = {Valter Uotila and Sven Groppe and Le Gruenwald and Jiaheng Lu and Wolfgang Mauerer},
	booktitle = {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},
	year = {2023},
	url = {https://ceur-ws.org/Vol-3462/QDSM1.pdf}
}
Tobias Winker, Umut Çalıkyılmaz, Le Gruenwald, and 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.
File: 3579142.3594299
Bibtex: BibTeX
@inproceedings{Winker2023QML_JOO,
	title = {Quantum Machine Learning for Join Order Optimization using Variational Quantum Circuits},
	author = {Tobias Winker and Umut Çalıkyılmaz and Le Gruenwald and Sven Groppe},
	booktitle = {Proceedings of the International Workshop on Big Data in Emergent Distributed Environments (BiDEDE), Seattle, WA, USA},
	year = {2023},
	url = {https://doi.org/10.1145/3579142.3594299}
}
Tobias Winker, Sven Groppe, Valter Uotila, Zhengtong Yan, Jiaheng Lu, Maja Franz, and 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.
File: 3555041.3589404
Bibtex: BibTeX
@inproceedings{SIGMOD23Tutorial,
author = {Tobias Winker and Sven Groppe and Valter Uotila and Zhengtong Yan and Jiaheng Lu and Maja Franz and Wolfgang Mauerer},
title = {Quantum Machine Learning: Foundation, New Techniques, and Opportunities for Database Research},
booktitle = {Proceedings of ACM SIGMOD/PODS International Conference on Management of Data (SIGMOD)},
location = {Seattle metropolitan area, Washington, USA},
year = {2023},
pages = {},
url = {https://doi.org/10.1145/3555041.3589404}
}

2022

Sven Groppe, Jinghua Groppe, Umut Çalıkyılmaz, Tobias Winker, and 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.
File: 978-3-031-35081-8_20