Scalable Online Data Management (SODATA) group, TU/e

The SODATA group in the Department of Mathematics and Computer Science at Eindhoven University of Technology studies data-intensive systems, focusing on how people and machines can effectively interact with massive, and possibly continuously generated data. Modern applications, ranging from online services and scientific instruments to smart infrastructure/IoT, produce data at volumes and speeds that exceed the capabilities of traditional data management and processing techniques, making timely analysis and decision-making increasingly difficult. Our group addresses this challenge by developing methods and systems that allow complex analytics and learning tasks to be performed in near-real-time (within milliseconds), and under stringent computational and memory constraints. We design approximate algorithms and compact data structures -— typically called synopses – that summarize high-volume data streams and time series using limited computational resources. In parallel, we design and implement distributed algorithms that scale efficiently across hundreds of machines. Our research provides the foundation for applications ranging from sensor-network analytics and large-scale similarity detection to, more recently, efficient and scalable machine-learning training.

Keywords

• Streaming algorithms and analytics
• Approximate query processing with synopses
• Time-series data management
• Scalable data systems

Collaboration opportunities

We actively seek collaborations with academic partners, research institutes, and not-for-profit organizations to tackle challenging problems aligned with our expertise. We also collaborate closely with industry, both through EU-funded projects and company-funded research. If you are interested in exploring a collaboration, we would be happy to hear from you.