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
Projectlead
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