Demo paper MM-mapsearch: Workload-Aware Mapping Selection receives Honorable Mention at EDBT 2026

The paper, authored by Pavel Koupil, Bedřich Mazourek, Jáchym Bártík, and Irena Holubová, presents a tool for selecting suitable mappings in multi-model databases. The method takes the expected query workload into account and explores schema variants across relational, document, and graph database systems.

The work shows how workload-aware optimization can help reduce unnecessary data migration and improve the design of multi-model data management systems.

Congratulations to the whole team.