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Schwerpunktprogramme

  • SPP 2037 Scalable Data Management for Future Hardware

    Over the last years, the social and commercial relevance of efficient data management has led to the development of database systems as ubiquitous and complex software systems. Hence there is a wide acceptance of architectural patterns for database systems which are based on assumptions on classic hardware setups.

    However, the currently used database concepts and systems are not well prepared to support emerging application domains such as eSciences, Industry 4.0, Internet of Things or Digital Humanities: From a user’s perspective flexible domain-specific query languages or at least access interfaces are requires; novel data models for these application domains have to be integrated; consistency guarantees which reduce flexibility and performance should be adaptable according to the requirements; and the volume and velocity of data caused by ubiquitous sensors have to be mastered by massive scalability and online processing. At the same time current and future hardware trends such as many-core CPUs, co-processors like GPU and FPGA, novel storage technologies like NVRAM and SSD as well as high-speed networks provide new opportunities.

    In order to open up the exemplarily mentioned application domains together with exploiting the potential of future hardware generations it becomes necessary now, to fundamentally rethink current database architectures. Thus, the objective of the priority program is to answer the scientific questions related to these issues. As a result, we expect the development and evaluation of architectures and abstractions for flexible and scalable data management techniques which provide extensibility regarding new data models including processing and access mechanisms for emerging applications, and exploit the features of modern and heterogeneous hardware as well as system-level services.

    . Beteiligt: Prof. Dr. Bernhard Seeger

    Teilprojekte:
    - Energieeffiziente Ereignisverarbeitung unter Verwendung moderner Hardware
    > PIs : Prof. Dr. Bernhard Seeger


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