Scalable Data Management for Future Hardware

Kai-Uwe Sattler is Full Professor for Database and Information Systems at the TU Ilmenau, Germany. He is the author and co-author of more than 300 publications and 9 textbooks in the field of database systems, algorithms, and data structures for data management. He is also the coordinator of the priority program, the results of which are presented in this book.

Alfons Kemper is Full Professor at the Technical University of Munich, Germany, and head of the Chair of Database Systems. His research group explores ways to optimize information systems for transactional and analytical applications to address the perpetual growth of data. He co-leads the development of the HyPer and the Umbra database systems, both internationally recognized as innovative high-performance database technology achievements.

Thomas Neumann is Full Professor at the Technical University of Munich, Germany, and head of the Chair of Data Science and Engineering. His research concentrates on database system development and query optimization. He has built several successful database systems in past, including the HyPer system and the Umbra system, and he has worked extensively on improving database systems design.

Jens Teubner is Full Professor and the head of the Databases and Information Systems Group at TU Dortmund. The focus of his research is the implementation of database systems on modern hardware architectures. He is the founder of Avalanche, a research project at ETH Zürich that has quickly become an international leader in the use of  FPGAs for database tasks.

1. ADAMANT: Hardware-Accelerated Query Processing Made Easy.- 2. Query Processing on Heterogeneous Hardware.- 3. Efficient Event Processing on Modern Hardware.- 4. Hybrid Transactional/Analytical Graph Processing in Modern Memory Hierarchies.- 5. MxKernel: A Bare-Metal Runtime System for Database Operations on Heterogeneous Many-Core Hardware.- 6. Scaling beyond DRAM without Compromising Performance.- 7. ReProVide: Query Optimisation and Near-Data Processing on Reconfigurable SoCs for Big Data Analysis.- 8. Scalable Data Management on Next-Generation Data Center Networks.- 9. Managing Very Large Data Sets on Directly-Attached NVMe Arrays.