Book Image

Redis Stack for Application Modernization

By : Luigi Fugaro, Mirko Ortensi
1 (1)
Book Image

Redis Stack for Application Modernization

1 (1)
By: Luigi Fugaro, Mirko 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)
1
Part 1: Introduction to Redis Stack
6
Part 2: Data Modeling
11
Part 3: From Development to Production

Redis Stack as a session store

Now that we have seen the principal features of the two main data structures that can be created, indexed, and searched in Redis Stack, let’s consider a conclusive example to understand what the Hash and JSON data structures offer to one of the most classical use cases: the session store. In Chapter 2, Developing Modern Use Cases with Redis Stack, we highlighted the importance of making session data available outside of the application server for different reasons, such as the scalability of the session store, high availability, load balancing, and, in the case of a session store that uses Redis as a backend, achieving real-time performance.

Redis offers many options to store and retrieve data efficiently. However, sessions store different types of data: metadata, lists, geographical locations, and entire objects. Finding the right data structure, using low-complexity data access patterns, and managing session expiration in a highly concurrent...