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Full Description
Simplify your first steps with the RavenDB NoSQL Document Database. This book takes a task-oriented approach by showing common problems, potential solutions, brief explanations of how those solutions work, and the mechanisms used. Based on real-world examples, the recipes in this book will show you how to solve common problems with Raven Query Language and will highlight reasons why RavenDB is a great choice for fast prototyping solutions that can sustain increasing amounts of data as your application grows.
Introducing RavenDB includes code and query examples that address real-life challenges you'll encounter when using RavenDB, helping you learn the basics of the Raven Query Language more quickly and efficiently. In many cases, you'll be able to copy and paste the examples into your own code, making only minor modifications to suit your application. RavenDB supports many advanced features, such full-text search, graph queries, and timeseries; recipes in the latter portion of the book will help you understand those advanced features and how they might be applied to your own code and applications.
After reading this book, you will be able to employ RavenDB's powerful features in your own projects.
What You Will Learn
Set up and start working with RavenDB
Model your objects for persistence in a NoSQL document database
Write basic and advanced queries in the Raven Query Language
Index your data using map/reduce techniques
Implement techniques leading to highly performant systems
Efficiently aggregate data and query on those aggregations
Who This Book Is For
Developers accustomed to relational databases who are about to enter a world of NoSQL databases. The book is also for experienced programmers who have used other non-relational databases and want to learn RavenDB. It will also prove useful for developers who want to move away from using Object-Relational Modeling frameworks and start working with a persistence solution that can store object graphs directly.
Contents
1. Getting Started with RavenDB.- 2. Document Modeling.- 3. Querying.- 4. Indexes.- 5. Map Indexes.- 6. MapReduce Indexes.- 7. Full-Text Search.
