Despite the growing interest in Real-Time Database Systems, there is no single book that acts as a reference to academics, professionals, and practitioners who wish to understand the issues involved in the design and development of RTDBS. Real-Time Database Systems: Issues and Applications fulfills this need. This book presents the spectrum of issues that may arise in various real-time database applications, the available solutions and technologies that may be used to address these issues, and the open problems that need to be tackled in the future. With rapid advances in this area, several concepts have been proposed without a widely accepted consensus on their definitions and implications. To address this need, the first chapter is an introduction to the key RTDBS concepts and definitions, which is followed by a survey of the state of the art in RTDBS research and practice. The remainder of the book consists of four sections: models and paradigms, applications and benchmarks, scheduling and concurrency control, and experimental systems. The chapters in each section are contributed by experts in the respective areas. Real-Time Database Systems: Issues and Applications is primarily intended for practicing engineers and researchers working in the growing area of real-time database systems. For practitioners, the book will provide a much needed bridge for technology transfer and continued education. For researchers, this book will provide a comprehensive reference for well-established results. This book can also be used in a senior or graduate level course on real-time systems, real-time database systems, and database systems or closely related courses.

In recent years, tremendous research has been devoted to the design of database systems for real-time applications, called real-time database systems (RTDBS), where transactions are associated with deadlines on their completion times, and some of the data objects in the database are associated with temporal constraints on their validity. Examples of important applications of RTDBS include stock trading systems, navigation systems and computer integrated manufacturing. Different transaction scheduling algorithms and concurrency control protocols have been proposed to satisfy transaction timing data temporal constraints. Other design issues important to the performance of a RTDBS are buffer management, index accesses and I/O scheduling. Real-Time Database Systems: Architecture and Techniques summarizes important research results in this area, and serves as an excellent reference for practitioners, researchers and educators of real-time systems and database systems.

This book provides an overview of both experimental and commercial real-time database systems (RTDBs) and a systematic approach to understanding, designing, and implementing them. To this end, the book is composed of four chapters: Chapter 1 “An Overview of Real-Time Database Systems” delves into the realm of RTDBs and discusses the specific requirements, transaction models, and scheduling algorithms that set RTDBs apart from conventional DBMs. Chapter 2 on “Experimental Real-Time Databases” presents various experimental RTDBs developed in academia with their architectures, features, and implementations, while chapter 3 on “Commercial Real-Time Databases” does so for systems developed and offered by commercial vendors as products or services. Eventually, chapter 4 on “Applications of Real-Time Database Systems” showcases various applications of RTDBs across different domains. This book will help researchers, graduate students and advanced professionals to get an overview of the area and to understand the main challenges and systems available.

Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth

The latest edition of a popular text and reference on database research, with substantial new material and revision; covers classical literature and recent hot topics. Lessons from database research have been applied in academic fields ranging from bioinformatics to next-generation Internet architecture and in industrial uses including Web-based e-commerce and search engines. The core ideas in the field have become increasingly influential. This text provides both students and professionals with a grounding in database research and a technical context for understanding recent innovations in the field. The readings included treat the most important issues in the database area--the basic material for any DBMS professional. This fourth edition has been substantially updated and revised, with 21 of the 48 papers new to the edition, four of them published for the first time. Many of the sections have been newly organized, and each section includes a new or substantially revised introduction that discusses the context, motivation, and controversies in a particular area, placing it in the broader perspective of database research. Two introductory articles, never before published, provide an organized, current introduction to basic knowledge of the field; one discusses the history of data models and query languages and the other offers an architectural overview of a database system. The remaining articles range from the classical literature on database research to treatments of current hot topics, including a paper on search engine architecture and a paper on application servers, both written expressly for this edition. The result is a collection of papers that are seminal and also accessible to a reader who has a basic familiarity with database systems.

The areas of active and real-time databases have seen a tremendous growth of interest in the past few years, particularly with regard to their support of time-critical and embedded applications. ARTDB-95 provided, therefore, an important forum for researchers from both communities to discuss research results, and also to chart new directions for the future. As well as the 11 submitted papers presented at the workshop, this volume also contains 4 invited papers on the following topics: the impact of active databases on commercial practice; the optimization of active database transactions; the need for better language, compiler and tool support for real-time databases; and the origin of time constraints associated with data, events and actions. Together the papers give a comprehensive overview of current research, and will provide invaluable reading for academic and industrial researchers and students at both undergraduate and postgraduate level.

Database systems of the next generation are likely to be inherently very complex due to the diversity of requirements placed on them. Incorporating active, real time, and temporal virtues in one database system is an arduous effort but is also a commend able one. This book presents the proceedings of the Second International Workshop on Active, Real Time, and Temporal Database Systems (ARTDB 97), held in Como, Milan, in September 1997. The aim of the workshop was to bring researchers together from the active and real time research communities, and to examine the current state of the art in active, real time, and temporal database systems. This book offers a collection of papers presented at the ARTDB 97 workshop. The papers, many of them representing proficient and tenable results, illuminate the feasibility of building database system supporting reactive behavior, while enforcing timeliness and predictability. The book contains nine papers carefully reviewed and accepted by the program committee, three invited papers written by prominent researchers in the field, and two summaries of the panel discussions held at the workshop. The program committee received seventeen submissions, where each submission was reviewed by at least three program committee members. The two panel sessions focused on predictability issues and on practical experience of active, real time, and temporal database systems. The ARTDB 97 workshop was held in cooperation with the IEEE Technical Committees on Real Time Systems and Complexity in Computing, and the ACM Special Interest Group on Manipulation of Data.