The fourth edition of this classic textbook provides major updates. This edition has completely new chapters on Big Data Platforms (distributed storage systems, MapReduce, Spark, data stream processing, graph analytics) and on NoSQL, NewSQL and polystore systems. It also includes an updated web data management chapter that includes RDF and semantic web discussion, an integrated database integration chapter focusing both on schema integration and querying over these systems. The peer-to-peer computing chapter has been updated with a discussion of blockchains. The chapters that describe classical distributed and parallel database technology have all been updated. The new edition covers the breadth and depth of the field from a modern viewpoint. Graduate students, as well as senior undergraduate students studying computer science and other related fields will use this book as a primary textbook. Researchers working in computer science will also find this textbook useful. This textbook has a companion web site that includes background information on relational database fundamentals, query processing, transaction management, and computer networks for those who might need this background. The web site also includes all the figures and presentation slides as well as solutions to exercises (restricted to instructors).

This third edition of a classic textbook can be used to teach at the senior undergraduate and graduate levels. The material concentrates on fundamental theories as well as techniques and algorithms. The advent of the Internet and the World Wide Web, and, more recently, the emergence of cloud computing and streaming data applications, has forced a renewal of interest in distributed and parallel data management, while, at the same time, requiring a rethinking of some of the traditional techniques. This book covers the breadth and depth of this re-emerging field. The coverage consists of two parts. The first part discusses the fundamental principles of distributed data management and includes distribution design, data integration, distributed query processing and optimization, distributed transaction management, and replication. The second part focuses on more advanced topics and includes discussion of parallel database systems, distributed object management, peer-to-peer data management, web data management, data stream systems, and cloud computing. New in this Edition: * New chapters, covering database replication, database integration, multidatabase query processing, peer-to-peer data management, and web data management. * Coverage of emerging topics such as data streams and cloud computing * Extensive revisions and updates based on years of class testing and feedback Ancillary teaching materials are available.

Object-oriented database management systems (OODBMSs) have generated significant excitement in the database community in the last decade. This interest stems from a real need for data management support for what are called "advanced application areas" that are not well-served by relational technology. The case for object-oriented technology has been made on three fronts. First is the data modeling requirements of the new applications. Some of the more important shortcomings of the relational systems in meeting the requirements of these applications include: 1. Relational systems deal with a single object type: a relation. A relation is used to model different real-world objects, but the semantics of this association is not part of the database. Furthermore, the attributes of a relation may come only from simple and fixed data type domains (numeric, character, and, sometimes, date types). Advanced applications require explicit storage and manipulation of more abstract types (e.g., images, design documents) and the ability for the users to define their own application-specific types. Therefore, a rich type system supporting user defined abstract types is required. 2. The relational model structures data in a relatively simple and flat manner. Non traditional applications require more complex object structures with nested objects (e.g., a vehicle object containing an engine object)."

The fourth edition of this classic textbook provides major updates. This edition has completely new chapters on Big Data Platforms (distributed storage systems, MapReduce, Spark, data stream processing, graph analytics) and on NoSQL, NewSQL and polystore systems. It also includes an updated web data management chapter that includes RDF and semantic web discussion, an integrated database integration chapter focusing both on schema integration and querying over these systems. The peer-to-peer computing chapter has been updated with a discussion of blockchains. The chapters that describe classical distributed and parallel database technology have all been updated. The new edition covers the breadth and depth of the field from a modern viewpoint. Graduate students, as well as senior undergraduate students studying computer science and other related fields will use this book as a primary textbook. Researchers working in computer science will also find this textbook useful. This textbook has a companion web site that includes background information on relational database fundamentals, query processing, transaction management, and computer networks for those who might need this background. The web site also includes all the figures and presentation slides as well as solutions to exercises (restricted to instructors).

This revised and expanded edition of Encyclopedia of Database Systems provides easy access to crucial concepts relevant to all aspects of very large databases, data management, and database systems, including areas of current interest and research results of historical significance. This comprehensive reference is organized alphabetically and each entry presents basic terminology, concepts, methods and algorithms, key results to date, references to the literature, and cross-references to other entries. Topics for the encyclopedia-including areas of current interest as well as research results of historical significance-were selected by a distinguished international advisory board and written by world-class experts in the field. New entries that reflect recent developments and technological advances in very large databases include: big data, big data technology, cloud computing, cloud data centers, business analytics, social networks, ranking, trust management, query over encrypted data, and more. Entirely new entries include database systems, relational database systems, databases, multimedia databases, bioinformatics, workflow systems, and web data management. Encyclopedia of Database Systems, 2nd edition, is designed to meet the needs of researchers, professors, graduate and undergraduate students in computer science and engineering. Industry professionals, from database specialists to software developers, will also benefit from this valuable reference work.