While FPGAs have seen prior use in database systems, in recent years interest in using
FPGA to accelerate databases has declined in both industry and academia for the following …

With modern computer architecture evolving, two problems conspire against the state-of-the-
art approaches in parallel query execution:(i) to take advantage of many-cores, all query …

Big data applications often incur large costs in I/O, data transfer and copying overhead,
especially when operating in cloud environments. Since most such computations are …

Analytical databases are continuously adapting to the underlying hardware in order to
saturate all sources of parallelism. At the same time, hardware evolves in multiple directions …

Evaluating the relational join is one of the central algorithmic and most well-studied
problems in database systems. A staggering number of variants have been considered …

The architectural changes introduced with multi-core CPUs have triggered a redesign of
main-memory join algorithms. In the last few years, two diverging views have appeared. One …

In this paper we experimentally study the performance of main-memory, parallel, multi-core
join algorithms, focusing on sort-merge and (radix-) hash join. The relative performance of …

GPUs have long been discussed as accelerators for database query processing because of
their high processing power and memory bandwidth. However, two main challenges limit the …

The explosive growth in digital data and its growing role in real-time decision support
motivate the design of high-performance database management systems (DBMSs) …

Two emerging hardware trends will dominate the database system technology in the near
future: increasing main memory capacities of several TB per server and massively parallel …