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 RAMCloud
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.
