Welcome to the website of the "Enterprise Platform and Integration Concepts" (EPIC) group.
Our activities are focused on the following research topics:
In-Memory Data Management for Enterprise Applications
Human-Centered Software Design and Engineering
In-Memory Data Management for Life Sciences
Our group includes PostDocs, PhD students, and student assistants, and is headed by Prof. Dr. Hasso Plattner. If you are interested in our work or want to join our team, please contact Dr. Matthias Uflacker.
Our team is giving a series of lectures and seminars with a focus on enterprise systems design and in-memory data management. Strong links to the industry ensure a close connection between theory and its implementation in the real world.
Our research focuses on the principles of in-memory data management on modern hardware and the integration of different hard- and software systems to meet business requirements. This involves studying the conceptual and technological aspects of modern enterprise applications as well as tools and methods for enterprise systems design.
We continually strive to translate our research into practical outputs that improve the quality of enterprise applications. A close link to industry partners ensures relevance and impact of our work. Get here an overview of our current and previous projects.
Boissier M, Schlosser R, Uflacker M. Hybrid Data Layouts for Tiered HTAP Databases with Pareto-Optimal Data Placements. 2018 IEEE 34th International Conference on Data Engineering (ICDE 2018).2018. p. 209-220.
Boissier M, Spivak A, Meyer C. Improving Materialization for Tiered Column-Stores: A Workload-Aware Ansatz Based on Table Reordering. ACSW '17 Proceedings of the Australasian Computer Science Week Multiconference, ACSW '17.New York, NY, USA: ACM;2017. p. 25:1-25:10.
Schlosser R, Boissier M. Optimal Price Reaction Strategies in the Presence of Active and Passive Competitors. Proceedings of the 6th International Conference on Operations Research and Enterprise Systems (ICORES), Porto, Portugal.2017. p. 47-56.
Zimmermann T, Djürken T, Mayer A, Janke M, Boissier M, Schwarz C, et al. Detecting Fraudulent Advertisements on a Large E-Commerce Platform. Proceedings of the Nineteenth International Workshop on Data Warehousing and OLAP, DOLAP, Venice, Italy, March 21, 2017.2017.
Serth S, Podlesny N, Bornstein M, Lindemann J, Latt J, Selke J, et al. An Interactive Platform to Simulate Dynamic Pricing Competition on Online Marketplaces. 21st IEEE International Enterprise Distributed Object Computing Conference, EDOC 2017, Quebec City, QC, Canada, October 10-13, 2017.IEEE;2017. p. 61-66.
Boissier M, Schlosser R, Podlesny N, Serth S, Bornstein M, Latt J, et al. Data-Driven Repricing Strategies in Competitive Markets: An Interactive Simulation Platform. Proceedings of the Eleventh ACM Conference on Recommender Systems (RecSys '17).New York, NY, USA: ACM;2017. p. 355-357.
Boissier M, Meyer C, Djürken T, Lindemann J, Mao K, Reinhardt P, et al. Analyzing Data Relevance and Access Patterns of Live Production Database Systems. Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, CIKM 2016.New York, NY, USA: ACM;2016. p. 2473--2475.
Schlosser R, Boissier M, Schober A, Uflacker M. How To Survive Dynamic Pricing Competition in E-commerce. Proceedings of the Poster Track of the 10th ACM Conference on Recommender Systems (RecSys 2016), Boston, USA, September 17, 2016.2016.
Faust M, Boissier M, Keller M, Schwalb D, Bischoff H, Eisenreich K, et al. Footprint Reduction and Uniqueness Enforcement with Hash Indices in SAP HANA. Database and Expert Systems Applications: 27th International Conference, DEXA 2016, Porto, Portugal, September 5-8, 2016, Proceedings, Part II.2016. p. 137--151.
Boissier M, Djürken T, Schlosser R, Faust M. A Cost-Aware and Workload-Based Index Advisor for Columnar In-Memory Databases. 22nd International Conference, ICIST 2016, Druskininkai, Lithuania, October 13-15, 2016, Proceedings, CCIS 639.2016. p. 285--299.
Boissier M, Meyer C, Uflacker M, Tinnefeld C. And all of a sudden: Main Memory Is Less Expensive Than Disk. Rabl T, Sachs K, Poess M, K. Baru C, Jacobsen H-A.Big Data Benchmarking. 1st edSpringer International Publishing;2015. p. 132-144.
Meyer C, Boissier M, Michaud A, Vollmer JO, Taylor K, Schwalb D, et al. Dynamic and Transparent Data Tiering for In-Memory Databases in Mixed Workload Environments. International Workshop on Accelerating Data Management Systems Using Modern Processor and Storage Architectures - ADMS @ VLDB 2015.2015.
Boissier M, Krüger J, Wust J, Plattner H. An Integrated Data Management for Enterprise Systems. ICEIS 2014 - Proceedings of the 16th International Conference on Enterprise Information Systems.2014. p. 410-418.
Krüger J, Hübner F, Wust J, Boissier M, Zeier A, Plattner H. Main Memory Databases for Enterprise Applications. IEEE 18Th International Conference on Industrial Engineering and Engineering Management (IE&EM), 2011.2011.
Krüger J, Grund M, Boissier M, Zeier A, Plattner H. Data Structures for Mixed Workloads in In-Memory Databases. 5th International Conference on Computer Sciences and Convergence Information Technology (ICCIT), 2010.2010.
We are proud to announce " A Course in In-Memory Data Management" by Prof. Dr. h.c. Hasso Plattner. This book is the culmination of six years work of in-memory research. As such, it provides the technical foundation for combined transactional and analytical workloads inside one single database as well as examples of new applications that are now possible given the availability of the new technology. The book is available at Springer.