Database replication is widely used for fault-tolerance, scalability and performance. The failure of one database replica does not stop the system from working as available replicas can take over the tasks of the failed replica. Scalability can be achieved by distributing the load across all replicas, and adding new replicas should the load increase. Finally, database replication can provide fast local access, even if clients are geographically distributed clients, if data copies are located close to clients. Despite its advantages, replication is not a straightforward technique to apply, and there are many hurdles to overcome. At the forefront is replica control: assuring that data copies remain consistent when updates occur. There exist many alternatives in regard to where updates can occur and when changes are propagated to data copies, how changes are applied, where the replication tool is located, etc. A particular challenge is to combine replica control with transaction management as it requires several operations to be treated as a single logical unit, and it provides atomicity, consistency, isolation and durability across the replicated system. The book provides a categorization of replica control mechanisms, presents several replica and concurrency control mechanisms in detail, and discusses many of the issues that arise when such solutions need to be implemented within or on top of relational database systems. Furthermore, the book presents the tasks that are needed to build a fault-tolerant replication solution, provides an overview of load-balancing strategies that allow load to be equally distributed across all replicas, and introduces the concept of self-provisioning that allows the replicated system to dynamically decide on the number of replicas that are needed to handle the current load. As performance evaluation is a crucial aspect when developing a replication tool, the book presents an analytical model of the scalability potential of various replication solution. For readers that are only interested in getting a good overview of the challenges of database replication and the general mechanisms of how to implement replication solutions, we recommend to read Chapters 1 to 4. For readers that want to get a more complete picture and a discussion of advanced issues, we further recommend the Chapters 5, 8, 9 and 10. Finally, Chapters 6 and 7 are of interest for those who want get familiar with thorough algorithm design and correctness reasoning. Table of Contents: Overview / 1-Copy-Equivalence and Consistency / Basic Protocols / Replication Architecture / The Scalability of Replication / Eager Replication and 1-Copy-Serializability / 1-Copy-Snapshot Isolation / Lazy Replication / Self-Configuration and Elasticity / Other Aspects of Replication

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Bettina Kemme is associate professor at the School of Computer Science of McGill University, Montreal, Canada. She received her undergraduate degree at the Friedrich-Alexander University in Erlangen, Germany, and her Ph.D. at the Swiss Federal Institute of Technology in Zurich (ETHZ). Her research focus lies in the design and development of distributed information systems, in particular, in data consistency aspects and the interplay between communication and data management. Her work on data replication is well known in the database and distributed systems communities. She has been PC member of many database and distributed systems conferences, such as VLDB, SIGMOD, ICDE, EDBT, Middleware, ICDCS, Eurosys, and P2P. She has been on the Editorial Board for the Encyclopedia of Database Systems, Springer, and track co-chair of ICDE 2009. She is area editor of Information Systems, Elsevier. Ricardo Jiménez Peris is associate professor at Universidad Politecnica de Madrid and co-director of the Distributed Systems Lab (LSD). He received his master and PhD degrees from Universidad Politecnica de Madrid. He was a visiting postdoc researcher at the Swiss Federal Institute of Technology in Zurich (ETHZ). His research interests have been around scalable and fault tolerant distributed systems and currently focusing on cloud computing. His research on scalable data replication during the last decade has obtained well-known results in the distributed systems and database communities. He is coordinator of the Stream European project on data stream cloud sys[1]tems. He has served as General chair at SRDS, Programme committee chair at EDCC, workshop chair at ICDCS, and tutorial chair at LADC, as well as Programme committee member at ICDCS, DSN, DISC, SRDS, EDCC among others. He has also been member of the expert group on cloud computing appointed by the European Commission. Marta Patiño-Martínez is associate professor at the Computer Science School of Universidad Politecnica de Madrid, Madrid, Spain. She received her master degree from Universidad Politecnica de Valencia, Spain and her PhD degree from Universidad Politecnica de Madrid. She was a visiting postdoc researcher at the Swiss Federal Institute of Technology in Zurich (ETHZ). Her research has focused on distributed systems with special emphasis on scalability and high availability. Her research on scalable data replication during the last 10 years has attracted the attention of many researchers from the distributed systems and database community. She is coordinator of the CumuloNimbo European project on cloud transactional systems. She has served in the Programme Committee of several distributed and database conferences such as VLDB, ICDCS, ICDE, SRDS, Middleware, and EDCC.