This book examines the field of parallel database management systems and
illustrates the great variety of solutions based on a shared-storage or
a shared-nothing architecture. Constantly dropping memory prices and the
desire to operate with low-latency responses on large sets of data paved
the way for main memory-based parallel database management systems.
However, this area is currently dominated by the shared-nothing approach
in order to preserve the in-memory performance advantage by processing
data locally on each server. The main argument this book makes is that
such an unilateral development will cease due to the combination of the
following three trends: a) Today's network technology features remote
direct memory access (RDMA) and narrows the performance gap between
accessing main memory on a server and of a remote server to and even
below a single order of magnitude. b) Modern storage systems scale
gracefully, are elastic and provide high-availability. c) A modern
storage system such as Stanford's RAM Cloud even keeps all data resident
in the main memory. Exploiting these characteristics in the context of a
main memory-based parallel database management system is desirable. The
book demonstrates that the advent of RDMA-enabled network technology
makes the creation of a parallel main memory DBMS based on a
shared-storage approach feasible.