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Redis Stack for Application Modernization

Redis Stack for Application Modernization

By : Luigi Fugaro, Ortensi
5 (2)
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Redis Stack for Application Modernization

Redis Stack for Application Modernization

5 (2)
By: Luigi Fugaro, Ortensi

Overview of this book

In modern applications, efficiency in both operational and analytical aspects is paramount, demanding predictable performance across varied workloads. This book introduces you to Redis Stack, an extension of Redis and guides you through its broad data modeling capabilities. With practical examples of real-time queries and searches, you’ll explore Redis Stack’s new approach to providing a rich data modeling experience all within the same database server. You’ll learn how to model and search your data in the JSON and hash data types and work with features such as vector similarity search, which adds semantic search capabilities to your applications to search for similar texts, images, or audio files. The book also shows you how to use the probabilistic Bloom filters to efficiently resolve recurrent big data problems. As you uncover the strengths of Redis Stack as a data platform, you’ll explore use cases for managing database events and leveraging introduce stream processing features. Finally, you’ll see how Redis Stack seamlessly integrates into microservices architectures, completing the picture. By the end of this book, you’ll be equipped with best practices for administering and managing the server, ensuring scalability, high availability, data integrity, stored functions, and more.
Table of Contents (18 chapters)
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1
Part 1: Introduction to Redis Stack
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Part 2: Data Modeling
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Chapter 8: Understanding Probabilistic Data Structures
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Part 3: From Development to Production
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Chapter 10: RedisInsight – the Data Management GUI
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Index
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Working with Hashes

The capabilities we’ve introduced so far have been explored through concise examples using cities and countries from the World dataset. In this section, we’ll consider a full-fledged use case, such as an application that stores and searches documents: a knowledge base (along the same lines, we could think of a learning management system, a blogging platform, or a generic and extensible content management system (CMS) or even a customer relationship management (CRM) tool). This kind of application works pretty well to present a walk-through of Redis Stack when used as a document store as we need solid classification and search capabilities to provide the best user experience, together with friendly user flows and, as usual, the real-time performance that is only possible when all the data is stored in the main memory. Let’s proceed to imagine what data we would store in our knowledge base to model a document:

  • The title.
  • The content...

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