Building a Columnar Database on RAMCloud: Database Design for the Low-Latency Enabled Data Center
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.
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Building a Columnar Database on RAMCloud: Database Design for the Low-Latency Enabled Data Center
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.
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Building a Columnar Database on RAMCloud: Database Design for the Low-Latency Enabled Data Center

Building a Columnar Database on RAMCloud: Database Design for the Low-Latency Enabled Data Center

by Christian Tinnefeld
Building a Columnar Database on RAMCloud: Database Design for the Low-Latency Enabled Data Center

Building a Columnar Database on RAMCloud: Database Design for the Low-Latency Enabled Data Center

by Christian Tinnefeld

Paperback(Softcover reprint of the original 1st ed. 2016)

$54.99 
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Overview

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.

Product Details

ISBN-13: 9783319373898
Publisher: Springer International Publishing
Publication date: 10/18/2017
Series: In-Memory Data Management Research
Edition description: Softcover reprint of the original 1st ed. 2016
Pages: 130
Product dimensions: 6.10(w) x 9.25(h) x 0.01(d)

About the Author

Dr. Christian Tinnefeld received his B.Sc. and M.Sc. degrees from the Hasso Plattner Institute at the University of Potsdam, Germany, where he also pursued his doctoral studies. His main research interests are In-Memory Databases and Cloud Computing. In the former area, he has been collaborating with SAP for six years and contributed to initial concepts of the SAP HANA database. In the latter area, Christian has been collaborating with the RAM Cloud Project at Stanford University, California, USA for three years.

Table of Contents

Part I: A Database System Architecture for a Shared Main Memory-Based Storage.- Part II: Database Operator Execution on a Shared Main Memory-Based Storage.- Part III: Evaluation.- Part IV: Conclusions.
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