Prof. Dr. h.c. mult. Hasso Plattner

Research and Implementation of Database Concepts

General Information

About this Seminar

Our database research seminar invites students that are interested in working on research-related topics in the area of database systems and, in particular, our research database systems Hyrise and Skyrise. An introduction is given in the Hyrise and Skyrise research papers and the open source Hyrise repository.

Example Topics

This list of topics is not exhaustive and we are happy to discuss research projects based on your previous experience and personal interests.

  • Incorporating Distributed Plans into Query Optimization: Query processing on scalable cloud infrastructure presents new opportunities and challenges for query optimization. A query optimizer for this environment may exploit the parallelism of the underlying infrastructure but must be aware of data partitioning, and thus data distribution and data shuffling during query execution. This project looks into rewrite rules for both logical and physical query plans, based on heuristics and costs.

Seminar Schedule

  1. Topics: During the first week of the lecture period, potential topics will be presented by the supervisors and chosen by the participants. The topics can be worked on alone or in groups of two.
  2. Familiarization: The participants are expected to familiarize themselves with the chosen topic and study recent publications that are provided by the supervisors.
  3. Project: Afterwards, implementations and evaluations will be conducted while participants receive guidance by the supervisors.
  4. Final Presentations of approximately 20 minutes (15 min. presentation + 5 min. Q&A) will be held at the end of the lecture period.
  5. Scientific Report: In the end, a scientific report (4-8 pages (depending on the group size) in IEEE format) should set the targeted problem into context (challenges, motivation, and related work), document the taken approach, and present evaluations as well as learnings to answer raised research questions.

Learning Goals

Participants will deepen their understanding of data management technologies, improve their system’s development skills by working with a large existing code base. Additionally, they will gain experience in the scientific method and writing, which will serve as a preparation for their upcoming master’s theses.


  • Good knowledge of C++ and/or Python
  • Basic knowledge of database systems (e.g., DBS or TuK I lectures)
  • Former attendance of the Develop Your Own Database seminar is beneficial but not obligatory


  • 50% project result and presentation
  • 40% scientific report
  • 10% personal engagement