Data management systems enable various influential applications from high-performance online services (e.g., social networks like Twitter and Facebook or financial markets) to big data analytics (e.g., scientific exploration, sensor networks, business intelligence). As a result, data management systems have been one of the main drivers for innovations in the database and computer architecture communities for several decades. Recent hardware trends require software to take advantage of the abundant parallelism existing in modern and future hardware. The traditional design of the data management systems, however, faces inherent scalability problems due to its tightly coupled components. In addition, it cannot exploit the full capability of the aggressive micro-architectural features of modern processors. As a result, today's most commonly used server types remain largely underutilized leading to a huge waste of hardware resources and energy. In this book, we shed light on the challenges present while running DBMS on modern multicore hardware. We divide the material into two dimensions of scalability: implicit/vertical and explicit/horizontal. The first part of the book focuses on the vertical dimension: it describes the instruction- and data-level parallelism opportunities in a core coming from the hardware and software side. In addition, it examines the sources of under-utilization in a modern processor and presents insights and hardware/software techniques to better exploit the microarchitectural resources of a processor by improving cache locality at the right level of the memory hierarchy. The second part focuses on the horizontal dimension, i.e., scalability bottlenecks of database applications at the level of multicore and multisocket multicore architectures. It first presents a systematic way of eliminating such bottlenecks in online transaction processing workloads, which is based on minimizing unbounded communication, and shows several techniques that minimize bottlenecks in major components of database management systems. Then, it demonstrates the data and work sharing opportunities for analytical workloads, and reviews advanced scheduling mechanisms that are aware of nonuniform memory accesses and alleviate bandwidth saturation.

"This volume contains 14 survey articles by reputed database researchers. They give an account of the state of the art, present research highlights and offer an outlook into the '90s regarding the most likely evolution of database technology-research, ad-tech, products and applications. The volume is structured into the following parts: - The evolution of database technology and its impact on enterprise information systems (keynote paper); - Demands on database systems in the '90s (office, engineering, science, multimedia, standardization); - User aspects (application programmers, ad hoc query users); - Database system and architecture concepts for novel applications (data models, object orientation, deductive DBMS, extensibility, data replication); - System and implementation aspects (performance and reliability, distributed and cooperative DBMS, hardware impact). The volume may serve as an orientation for all those who are interested in database systems and their impact on computer applications."--PUBLISHER'S WEBSITE.

Data management systems enable various influential applications from high-performance online services (e.g., social networks like Twitter and Facebook or financial markets) to big data analytics (e.g., scientific exploration, sensor networks, business intelligence). As a result, data management systems have been one of the main drivers for innovations in the database and computer architecture communities for several decades. Recent hardware trends require software to take advantage of the abundant parallelism existing in modern and future hardware. The traditional design of the data management systems, however, faces inherent scalability problems due to its tightly coupled components. In addition, it cannot exploit the full capability of the aggressive micro-architectural features of modern processors. As a result, today's most commonly used server types remain largely underutilized leading to a huge waste of hardware resources and energy. In this book, we shed light on the challenges present while running DBMS on modern multicore hardware. We divide the material into two dimensions of scalability: implicit/vertical and explicit/horizontal. The first part of the book focuses on the vertical dimension: it describes the instruction- and data-level parallelism opportunities in a core coming from the hardware and software side. In addition, it examines the sources of under-utilization in a modern processor and presents insights and hardware/software techniques to better exploit the microarchitectural resources of a processor by improving cache locality at the right level of the memory hierarchy. The second part focuses on the horizontal dimension, i.e., scalability bottlenecks of database applications at the level of multicore and multisocket multicore architectures. It first presents a systematic way of eliminating such bottlenecks in online transaction processing workloads, which is based on minimizing unbounded communication, and shows several techniques that minimize bottlenecks in major components of database management systems. Then, it demonstrates the data and work sharing opportunities for analytical workloads, and reviews advanced scheduling mechanisms that are aware of nonuniform memory accesses and alleviate bandwidth saturation.

Architecture of a Database System presents an architectural discussion of DBMS design principles, including process models, parallel architecture, storage system design, transaction system implementation, query processor and optimizer architectures, and typical shared components and utilities.

This textbook examines database systems from the viewpoint of a software developer. This perspective makes it possible to investigate why database systems are the way they are. It is of course important to be able to write queries, but it is equally important to know how they are processed. We e.g. don’t want to just use JDBC; we also want to know why the API contains the classes and methods that it does. We need a sense of how hard is it to write a disk cache or logging facility. And what exactly is a database driver, anyway? The first two chapters provide a brief overview of database systems and their use. Chapter 1 discusses the purpose and features of a database system and introduces the Derby and SimpleDB systems. Chapter 2 explains how to write a database application using Java. It presents the basics of JDBC, which is the fundamental API for Java programs that interact with a database. In turn, Chapters 3-11 examine the internals of a typical database engine. Each chapter covers a different database component, starting with the lowest level of abstraction (the disk and file manager) and ending with the highest (the JDBC client interface); further, the respective chapter explains the main issues concerning the component, and considers possible design decisions. As a result, the reader can see exactly what services each component provides and how it interacts with the other components in the system. By the end of this part, s/he will have witnessed the gradual development of a simple but completely functional system. The remaining four chapters then focus on efficient query processing, and focus on the sophisticated techniques and algorithms that can replace the simple design choices described earlier. Topics include indexing, sorting, intelligent buffer usage, and query optimization. This text is intended for upper-level undergraduate or beginning graduate courses in Computer Science. It assumes that the reader is comfortable with basic Java programming; advanced Java concepts (such as RMI and JDBC) are fully explained in the text. The respective chapters are complemented by “end-of-chapter readings” that discuss interesting ideas and research directions that went unmentioned in the text, and provide references to relevant web pages, research articles, reference manuals, and books. Conceptual and programming exercises are also included at the end of each chapter. Students can apply their conceptual knowledge by examining the SimpleDB (a simple but fully functional database system created by the author and provided online) code and modifying it.

"Information Systems for Business and Beyond introduces the concept of information systems, their use in business, and the larger impact they are having on our world."--BC Campus website.

Covers the important requirements of teaching databases with a modular and progressive perspective. This book can be used for a full course (or pair of courses), but its first half can be profitably used for a shorter course.

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 Design and Implementation of Modern Column-Oriented Database Systems discusses modern column-stores, their architecture and evolution as well the benefits they can bring in data analytics.

When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it’s often difficult to understand what each one offers and how they differ. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals. Throughout the book, you’ll explore relevant material gleaned from numerous books, papers, blog posts, and the source code of several open source databases. These resources are listed at the end of parts one and two. You’ll discover that the most significant distinctions among many modern databases reside in subsystems that determine how storage is organized and how data is distributed. This book examines: Storage engines: Explore storage classification and taxonomy, and dive into B-Tree-based and immutable Log Structured storage engines, with differences and use-cases for each Storage building blocks: Learn how database files are organized to build efficient storage, using auxiliary data structures such as Page Cache, Buffer Pool and Write-Ahead Log Distributed systems: Learn step-by-step how nodes and processes connect and build complex communication patterns Database clusters: Which consistency models are commonly used by modern databases and how distributed storage systems achieve consistency