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GraphQueryML – Using Machine Learning to Optimize Queries in Graph Databases (SNSF/DFG)

Description

Optimizing the brain of databases with machine learning:Query optimization is one of the hardest problems of database systems research. A query optimizer can be considered as the “brain” of the system that makes sure that queries are executed efficiently. Even after several decades of research, many sub-problems of query optimization are still unsolved. The goal of this project is to use machine learning to improve the “brain” of relational database systems as well as graph database systems.

Key Data

Deputy Projectlead

Prof. Dr. Michael Grossniklaus

Project team

Dennis Gehrig, Claude Lehmann, Dr. Pavel Sulimov, Prof. Dr. Ce Zhang

Project partners

Universität Konstanz; Eidgenössische Technische Hochschule Zürich ETH

Project status

ongoing, started 07/2021

Funding partner

SNF-Projektförderung / Projekt Nr. 192105; Deutsche Forschungsgemeinschaft DFG / Projekt Nr. 441617860

Project budget

539'000 EUR