The database field has experienced a rapid and incessant growth since the development of relational databases. The progress in database systems and applications has produced a diverse landscape of specialized technology areas that have often become the exclusive domain of research specialists. Examples include active databases, temporal databases, object-oriented databases, deductive databases, imprecise reasoning and queries, and multimedia information systems. This book provides a systematic introduction to and an in-depth treatment of these advanced database areas. It supplies practitioners and researchers with authoritative coverage of recent technological advances that are shaping the future of commercial database systems and intelligent information systems. Advanced Database Systems was written by a team of six leading specialists who have made significant contributions to the development of the technology areas covered in the book. Benefiting from the authors' long experience teaching graduate and professional courses, this book is designed to provide a gradual introduction to advanced research topics and includes many examples and exercises to support its use for individual study, desk reference, and graduate classroom teaching.

Database management is attracting wide interest in both academic and industrial contexts. New application areas such as CAD/CAM, geographic information systems, and multimedia are emerging. The needs of these application areas are far more complex than those of conventional business applications. The purpose of this book is to bring together a set of current research issues that addresses a broad spectrum of topics related to database systems and applications. The book is divided into four parts: - object-oriented databases, - temporal/historical database systems, - query processing in database systems, - heterogeneity, interoperability, open system architectures, multimedia database systems.

Recent years have seen an explosive growth in the use of new database applications such as CAD/CAM systems, spatial information systems, and multimedia information systems. The needs of these applications are far more complex than traditional business applications. They call for support of objects with complex data types, such as images and spatial objects, and for support of objects with wildly varying numbers of index terms, such as documents. Traditional indexing techniques such as the B-tree and its variants do not efficiently support these applications, and so new indexing mechanisms have been developed. As a result of the demand for database support for new applications, there has been a proliferation of new indexing techniques. The need for a book addressing indexing problems in advanced applications is evident. For practitioners and database and application developers, this book explains best practice, guiding the selection of appropriate indexes for each application. For researchers, this book provides a foundation for the development of new and more robust indexes. For newcomers, this book is an overview of the wide range of advanced indexing techniques. Indexing Techniques for Advanced Database Systems is suitable as a secondary text for a graduate level course on indexing techniques, and as a reference for researchers and practitioners in industry.

Advanced Database Indexing begins by introducing basic material on storage media, including magnetic disks, RAID systems and tertiary storage such as optical disk and tapes. Typical access methods (e.g. B+ trees, dynamic hash files and secondary key retrieval) are also introduced. The remainder of the book discusses recent advances in indexing and access methods for particular database applications. More specifically, issues such as external sorting, file structures for intervals, temporal access methods, spatial and spatio-temporal indexing, image and multimedia indexing, perfect external hashing methods, parallel access methods, concurrency issues in indexing and parallel external sorting are presented for the first time in a single book. Advanced Database Indexing is an excellent reference for database professionals and may be used as a text for advanced courses on the topic.

The objective of this book is to address the advanced and emerging topics of modern database systems starting from the inception. This book is developed as a text book for the compulsory subject Database System / Database Management System / Advanced Database System of B. Tech/B.E, M.C.A and other courses of Computer Science and Engineering, Software Engineering and Information Technology. In this book, total 17 chapters have been included, namely, Introduction to Database Management System, Fundamentals of Database Management System, Conceptual Data Modeling, The Relational Data Model, Normalization, Relational Query Languages, Transaction Management & Concurrency Control, Database Recovery and Security, Query Processing, Parallel Database System, Distributed Database System - Concepts & Design, Object-Oriented Databases, Spatial Database System, Temporal and Statistical Database Systems, Data Warehousing, Data Mining, and Cloud Computing. Recent AICTE approved syllabus of B.Tech/B.E and MCA has been consulted for preparation of the content of the book. This book is intended for those who are professionally interested in advanced database concepts including students and teachers of computer science, software engineering and information technology, researchers, application developers, and analysts.

Mining Very Large Databases with Parallel Processing addresses the problem of large-scale data mining. It is an interdisciplinary text, describing advances in the integration of three computer science areas, namely `intelligent' (machine learning-based) data mining techniques, relational databases and parallel processing. The basic idea is to use concepts and techniques of the latter two areas - particularly parallel processing - to speed up and scale up data mining algorithms. The book is divided into three parts. The first part presents a comprehensive review of intelligent data mining techniques such as rule induction, instance-based learning, neural networks and genetic algorithms. Likewise, the second part presents a comprehensive review of parallel processing and parallel databases. Each of these parts includes an overview of commercially-available, state-of-the-art tools. The third part deals with the application of parallel processing to data mining. The emphasis is on finding generic, cost-effective solutions for realistic data volumes. Two parallel computational environments are discussed, the first excluding the use of commercial-strength DBMS, and the second using parallel DBMS servers. It is assumed that the reader has a knowledge roughly equivalent to a first degree (BSc) in accurate sciences, so that (s)he is reasonably familiar with basic concepts of statistics and computer science. The primary audience for Mining Very Large Databases with Parallel Processing is industry data miners and practitioners in general, who would like to apply intelligent data mining techniques to large amounts of data. The book will also be of interest to academic researchers and postgraduate students, particularly database researchers, interested in advanced, intelligent database applications, and artificial intelligence researchers interested in industrial, real-world applications of machine learning.

Market_Desc: This book is a valuable source of information for academics, practitioners, post and under graduate students with a good overview of basic notions, methods and techniques, as well as important issues and trends across the broad spectrum of data management. Special Features: · Provides simple, clear and concise language, which makes the book easy and enjoyable to read.· Follows a code centric approach and provides code snippets wherever applicable.· Provides well-structured text and illustrative block diagrams and figures wherever required.· Provides case studies involving the latest technologies, such as Java, J2EE, and ASP.NET with backend database, such as Oracle and SQL Server with clear illustrations and step-wise approach on how to develop a real-life project.· Includes chapter objectives and advance organizer at the beginning of each chapter to describe what the reader would learn in the chapter.· Includes comprehensive and detailed coverage of each topic to meet the requirements of the target audience, including postgraduates, undergraduates, and professionals. About The Book: This book provides a systematic approach with an in-depth analysis of advanced database areas as well as the basics of database management systems. It explores the different normalization techniques starting from the very basic first normal form and extends up to sixth normal form. The theme of this book is the potential of new advanced database systems. This book combines advanced techniques with practical advice and many new ideas, methods, and examples for database management students, system specialists, and programmers. It provides a wealth of technical information on database methods and an encyclopedic coverage of advanced techniques. Summing up, this book is a valuable source of information for academics, practitioners, post and under graduate students with a good overview of basic notions, methods and techniques, as well as important issues and trends across the broad spectrum of data management.

Active database systems enhance traditional database functionality with powerful rule-processing capabilities, providing a uniform and efficient mechanism for many database system applications. Among these applications are integrity constraints, views, authorization, statistics gathering, monitoring and alerting, knowledge-based systems, expert systems, and workflow management. This significant collection focuses on the most prominent research projects in active database systems. The project leaders for each prototype system provide detailed discussions of their projects and the relevance of their results to the future of active database systems. Features: A broad overview of current active database systems and how they can be extended and improved A comprehensive introduction to the core topics of the field, including its motivation and history Coverage of active database (trigger) capabilities in commercial products Discussion of forthcoming standards

This text goes beyond the relational coverage of a typical first course in databases. Dietrich and Urban include object-oriented conceptual data modeling, object oriented databases, and databases and the Web. Topic coverage is in-depth and accessible to undergraduates as well as graduate CS students. Teachers can select the topics that best fit their course.

Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.