This book examines the key principles, algorithms, and trade-offs of data systems, using the internals of various popular software packages and frameworks as examples.

You’ll learn how to determine what kind of tool is appropriate for which purpose, and how certain tools can be combined to form the foundation of a good application architecture. You’ll learn how to develop an intuition for what your systems are doing, so that you’re better able to track down any problems that arise.

Using hundreds of illustrations and an elegant intuitive modeling language, the authors present a methodology that fully exploits the conceptual modeling approach of software engineering, from idea to application. Readers will learn not only how to harness the design technologies of relational databases for use on the Web, but also how to transform their conceptual designs of data-intensive Web applications into effective software components

Table of Contents
About the Author
About this Book
Part I. The Big Picture
Chapter 1. Reliable, Scalable and Maintainable Applications
Thinking About Data Systems
Reliability
Scalability
Maintainability
Chapter 2. The Battle of the Data Models
Rivals of the Relational Model
Query Languages for Data
Graph-like Data Models
Chapter 3. Storage and Retrieval
Data Structures that Power Your Database
Transaction Processing or Analytics?
Column-oriented storage
Part II. Systems of Record
Chapter 4. Replication
Shared-Nothing Architectures
Leaders and Followers
Problems With Replication Lag
Beyond leader-based replication

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