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.

Now in its third edition, this best-selling book continues to bring you some of the best thinking on how to apply Oracle Database to produce scalable applications that perform well and deliver correct results. Tom Kyte and Darl Kuhn share a simple philosophy: "you can treat Oracle as a black box and just stick data into it, or you can understand how it works and exploit it as a powerful computing environment." If you choose the latter, then you’ll find that there are few information management problems that you cannot solve quickly and elegantly. This fully revised third edition covers the developments up to Oracle Database 12c. Significant new content is included surrounding Oracle's new cloud feature set, and especially the use of pluggable databases. Each feature is taught in a proof-by-example manner, not only discussing what it is, but also how it works, how to implement software using it, and the common pitfalls associated with it. Don’t treat Oracle Database as a black-box. Get this book. Get under the hood. Turbo-charge your career. Revised to cover Oracle Database 12c Proof-by-example approach: Let the evidence be your guide Dives deeply into Oracle Database’s most powerful features

Data Architecture: From Zen to Reality explains the principles underlying data architecture, how data evolves with organizations, and the challenges organizations face in structuring and managing their data. Using a holistic approach to the field of data architecture, the book describes proven methods and technologies to solve the complex issues dealing with data. It covers the various applied areas of data, including data modelling and data model management, data quality, data governance, enterprise information management, database design, data warehousing, and warehouse design. This text is a core resource for anyone customizing or aligning data management systems, taking the Zen-like idea of data architecture to an attainable reality. The book presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios. It teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions. It includes the detail needed to illustrate how the fundamental principles are used in current business practice. The book is divided into five sections, one of which addresses the software-application development process, defining tools, techniques, and methods that ensure repeatable results. Data Architecture is intended for people in business management involved with corporate data issues and information technology decisions, ranging from data architects to IT consultants, IT auditors, and data administrators. It is also an ideal reference tool for those in a higher-level education process involved in data or information technology management. - Presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios - Teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions - Includes the detail needed to illustrate how the fundamental principles are used in current business practice

The book 'Distributed Database Architecture' discusses various topics related to the database architecture. The technology of database management is a very commonly used one nowadays and is the basis of many tech-businesses. The book takes the readers through the various aspects of the distributed database architecture, the way in which it is designed and th manner in which it is brought to use. The book can be used a good source of information by the various IT professionals or aspiring the data analysts.

Now in its fourth edition and covering Oracle Database 21c, this best-selling book continues to bring you some of the best thinking on how to apply Oracle Database to produce scalable applications that perform well and deliver correct results. Tom Kyte and Darl Kuhn share a simple philosophy: "you can treat Oracle as a black box and just stick data into it, or you can understand how it works and exploit it as a powerful computing environment." If you choose the latter, then you’ll find that there are few information management problems that you cannot solve quickly and elegantly. This fully revised fourth edition covers the developments and new features up to Oracle Database 21c. Up-to-date features are covered for tables, indexes, data types, sequences, partitioning, data loading, temporary tables, and more. All the examples are demonstrated using modern techniques and are executed in container and pluggable databases. The book’s proof-by-example approach encourages you to let evidence be your guide. Try something. See the result. Understand why the result is what it is. Apply your newfound knowledge with confidence. The book covers features by explaining how each one works, how to implement software using it, and the common pitfalls associated with it. Don’t treat Oracle Database as a black box. Get this book. Dive deeply into Oracle Database’s most powerful features that many do not invest the time to learn about. Set yourself apart from your competition and turbo-charge your career. What You Will Learn Identify and effectively resolve application performance issues and bottlenecks Architect systems to leverage the full power and feature set of Oracle’s database engine Configure a database to maximize the use of memory structures and background processes Understand internal locking and latching technology and how it impacts your system Proactively recommend best practices around performance for table and index structures Take advantage of advanced features such as table partitioning and parallel execution Who This Book Is For Oracle developers and Oracle DBAs. If you’re a developer and want a stronger understanding of Oracle features and architecture that will enable your applications to scale regardless of the workload, this book is for you. If you’re a DBA and want to intelligently work with developers to design applications that effectively leverage Oracle technology, then look no further.

Now in its second edition, this best-selling book by Tom Kyte of "Ask Tom" fame continues to bring you some of the best thinking on how to apply Oracle Database to produce scalable applications that perform well and deliver correct results. Tom has a simple philosophy: you can treat Oracle as a black box and just stick data into it or you can understand how it works and exploit it as a powerful computing environment. If you choose the latter, then you’ll find that there are few information management problems that you cannot solve quickly and elegantly. This fully revised second edition covers the developments up to Oracle Database 11g. Each feature is taught in a proof-by-example manner, not only discussing what it is, but also how it works, how to implement software using it, and the common pitfalls associated with it. Don’t treat Oracle Database as a black-box. Get this book. Get under the hood. Turbo-charge your career. Fully revised to cover Oracle Database 11g Proof-by-example approach: Let the evidence be your guide Dives deeply into Oracle Database’s most powerful features

How can you realize MySQL's full power? With High Performance MySQL, you'll learn advanced techniques for everything from setting service-level objectives to designing schemas, indexes, and queries to tuning your server, operating system, and hardware to achieve your platform's full potential. This guide also teaches database administrators safe and practical ways to scale applications through replication, load balancing, high availability, and failover. Updated to reflect recent advances in cloud- and self-hosted MySQL, InnoDB performance, and new features and tools, this revised edition helps you design a relational data platform that will scale with your business. You'll learn best practices for database security along with hard-earned lessons in both performance and database stability. Dive into MySQL's architecture, including key facts about its storage engines Learn how server configuration works with your hardware and deployment choices Make query performance part of your software delivery process Examine enhancements to MySQL's replication and high availability Compare different MySQL offerings in managed cloud environments Explore MySQL's full stack optimization from application-side configuration to server tuning Turn traditional database management tasks into automated processes

A comprehensive guide to design, build and execute effective Big Data strategies using Hadoop Key Features -Get an in-depth view of the Apache Hadoop ecosystem and an overview of the architectural patterns pertaining to the popular Big Data platform -Conquer different data processing and analytics challenges using a multitude of tools such as Apache Spark, Elasticsearch, Tableau and more -A comprehensive, step-by-step guide that will teach you everything you need to know, to be an expert Hadoop Architect Book Description The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools. This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster. By the end of this book, you will have all the knowledge you need to build expert Big Data systems. What you will learn Build an efficient enterprise Big Data strategy centered around Apache Hadoop Gain a thorough understanding of using Hadoop with various Big Data frameworks such as Apache Spark, Elasticsearch and more Set up and deploy your Big Data environment on premises or on the cloud with Apache Ambari Design effective streaming data pipelines and build your own enterprise search solutions Utilize the historical data to build your analytics solutions and visualize them using popular tools such as Apache Superset Plan, set up and administer your Hadoop cluster efficiently Who this book is for This book is for Big Data professionals who want to fast-track their career in the Hadoop industry and become an expert Big Data architect. Project managers and mainframe professionals looking forward to build a career in Big Data Hadoop will also find this book to be useful. Some understanding of Hadoop is required to get the best out of this book.

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