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

Bachelor Project HP1 - In-Memory Data Management for Enhanced ERP


Earlier bachelor projects focused on how an in-memory data layer can change the way “traditional” transactional enterprise applications work. By eliminating redundantly stored aggregates, views, and indices, the applications became 10-100 times faster while extending application functionality and improving flexibility. Furthermore, the in-memory data management enables analytics on the transactional data and eliminates costly transformations to external data warehouses. Consequently, a set of totally new applications becomes feasible with reduced total cost of ownership as a side effect. These applications enable businesses to get  real-time insights, make more confident decisions, anticipate and react to changing conditions, and to become more flexible while being more effective by taking advantage of their data.


Based on disruptive technology changes introduced by SAP’s in-memory database HANA, enterprise applications are adjusted for new programming paradigms while old constraints fall away. The project will rethink the way enterprise applications are designed and how they can be built leveraging new patterns and algorithms for in-memory databases, modern hardware architectures with large amounts of main memory, and multi-core processors. For instance, we will evaluate logical database schemas, which are designed for the fast scan performances of in-memory databases. Furthermore, we will focus on the interface between applications and databases and investigate how object relational mappers can be used for analytical scenarios. The project team will implement a prototype application with a web-based user interface on top of our research prototype HYRISE or SAP’s in-memory database HANA. During the project, the team will be supported by SAP.