June 17 – 22 , 2018, Dagstuhl Seminar 18251

Database Architectures for Modern Hardware


Peter A. Boncz (CWI – Amsterdam, NL)
Goetz Graefe (Google – Madison, US)
Bingsheng He (National University of Singapore, SG)
Kai-Uwe Sattler (TU Ilmenau, DE)

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Annette Beyer for administrative matters

Michael Gerke for scientific matters


Over the last years, the social and commercial relevance of efficient data management has led to the development of database systems as foundation of almost all 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, Internet of Things or Digital Humanities. From a user's perspective, flexible domain-specific query languages or at least access interfaces are required, novel data models for these application domains have to be integrated, and consistency guarantees which reduce flexibility and performance should be adaptable according to the requirements. Finally, volume, variety, veracity as well as velocity of data caused by ubiquitous sensors have to be mastered by massive scalability and online processing by providing traditional qualities of database systems like consistency, isolation and descriptive query languages. At the same time, current and future hardware trends provide new opportunities such as many-core CPUs with hundreds of compute cores, special-purpose computing units such as GPUs and FPGAs, novel storage technologies such as non-volatile memory and advanced solid state devices, as well as high-speed networks based on 10 Gbit/s Ethernet or InfiniBand supporting already direct access to memory of a remote node. Moreover, heterogeneous hardware designs such as coupled CPU-FPGA and CPU-GPU architectures represent a trend of close integration between classic hardware and emerging hardware.

Thus, the goal of this Dagstuhl Seminar is to bring together researchers and practitioners from these areas representing both the software and hardware sides and therefore different disciplines to foster cross-cutting architectural discussions. During the seminar, the participants discuss opportunities and challenges in order to exploit features of modern hardware and operating system primitives for data processing as well as to support and accelerate modern database processing by hardware technology. Having a dialogue between the different disciplines allows for a push-and-pull principle: Database researchers may learn about research opportunities of current developments of emerging hardware as well as may propose requirements to lower-level hardware and software components. The seminar extends the series of previous Dagstuhl seminars on database systems aspects, such as "Robust Query Processing" (10381, 12321, 17222) as well as "Databases on Future Hardware" (17101).

The seminar will start with a focus on specific problems of hardware accelerated database processing and on prior results. Thereafter, seminar participants will work in small groups on selected cross-cutting problems. Possible topics are specific query processing techniques for FPGA, GPU, and many-core processors, exploiting new memory and storage technologies for indexing and recovery, hardware support for concurrency control and transaction management or the impact of high-speed networks on distributed database architectures. Every day, interleaved plenary presentations and discussions will re-focus the working groups. Towards the end of the week, we may have concrete ideas for new techniques and perhaps for publications. Both academic and industrial participants may freely use the discussion contents and results for follow-on work.

  Creative Commons BY 3.0 DE
  Peter A. Boncz, Goetz Graefe, Bingsheng He, and Kai-Uwe Sattler


  • Data Bases / Information Retrieval
  • Data Structures / Algorithms / Complexity
  • Hardware


  • Database systems
  • Computer Architecture
  • Hardware Support for Databases
  • Co-Processors
  • Non-Volatile Memory

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