Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

Part of: Synthesis digital library of engineering and computer science.

Series from website.

Includes bibliographical references (p. 107-117).

Preface -- Acknowledgments --

1. Introduction --

2. Distributed data management -- 2.1 Distributed systems -- 2.1.1 Logical time and Lamport clocks -- 2.1.2 Vector clocks -- 2.1.3 Mutual exclusion and quorums -- 2.1.4 Leader election -- 2.1.5 Group communication through broadcast and multicast -- 2.1.6 The consensus problem -- 2.1.7 CAP theorem -- 2.2 Peer to peer systems -- 2.3 Database systems -- 2.3.1 Preliminaries -- 2.3.2 Concurrency control -- 2.3.3 Recovery and commitment --

3. Cloud data management: early trends -- 3.1 Overview of key-value stores -- 3.2 Design choices and their implications -- 3.2.1 Data model -- 3.2.2 Data distribution and request routing -- 3.2.3 Cluster management -- 3.2.4 Fault-tolerance and data replication -- 3.3 Key-value store system examples -- 3.3.1 Bigtable -- 3.3.2 PNUTS -- 3.3.3 Dynamo -- 3.4 Discussion --

4. Transactions on co-located data -- 4.1 Data or ownership co-location -- 4.1.1 Leveraging schema patterns -- 4.1.2 Access-driven database partitioning -- 4.1.3 Application-specified dynamic partitioning -- 4.2 Transaction execution -- 4.3 Data storage -- 4.3.1 Coupled storage -- 4.3.2 Decoupled storage -- 4.4 Replication -- 4.4.1 Explicit replication -- 4.4.2 Implicit replication -- 4.5 A survey of the systems -- 4.5.1 G-store -- 4.5.2 ElasTraS -- 4.5.3 Cloud SQL server -- 4.5.4 Megastore -- 4.5.5 Relational cloud -- 4.5.6 Hyder -- 4.5.7 Deuteronomy --

5. Transactions on distributed data -- 5.1 Database-like functionality on cloud storage -- 5.2 Transactional support for geo-replicated data -- 5.3 Incremental update processing using distributed transactions -- 5.4 Scalable distributed synchronization using minitransactions -- 5.5 Discussion --

6. Multi-tenant database systems -- 6.1 Multi-tenancy models -- 6.1.1 Shared hardware -- 6.1.2 Shared process -- 6.1.3 Shared table -- 6.1.4 Analyzing the models -- 6.2 Database elasticity in the cloud -- 6.2.1 Albatross: live migration for shared storage data stores -- 6.2.2 Zephyr: live migration for shared nothing data stores -- 6.2.3 Slacker: live DBMS instance migration in shared-nothing model -- 6.3 Autonomic control for database workloads in the cloud -- 6.4 Discussion --

7. Concluding remarks -- Bibliography -- Authors' biographies.

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Cloud computing has emerged as a successful paradigm of service-oriented computing and has revolutionized the way computing infrastructure is used. This success has seen a proliferation in the number of applications that are being deployed in various cloud platforms. There has also been an increase in the scale of the data generated as well as consumed by such applications. Scalable database management systems form a critical part of the cloud infrastructure.The attempt to address the challenges posed by the management of big data has led to a plethora of systems. This book aims to clarify some of the important concepts in the design space of scalable data management in cloud computing infrastructures. Some of the questions that this book aims to answer are: the appropriate systems for a specific set of application requirements, the research challenges in data management for the cloud, and what is novel in the cloud for database researchers? We also aim to address one basic question: whether cloud computing poses new challenges in scalable data management or it is just a reincarnation of old problems? We provide a comprehensive background study of state-of-the-art systems for scalable data management and analysis. We also identify important aspects in the design of different systems and the applicability and scope of these systems. A thorough understanding of current solutions and a precise characterization of the design space are essential for clearing the "cloudy skies of data management" and ensuring the success of DBMSs in the cloud, thus emulating the success enjoyed by relational databases in traditional enterprise settings.

Also available in print.

Title from PDF t.p. (viewed on January 18, 2013).