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

Summary

In this chapter, we have explored various Redis client libraries and OM solutions across five popular programming languages: Python, Java, JavaScript, C#, and Go..

For Python, we learned about redis-py, a widely used Redis client library that provides an easy-to-use interface for interacting with Redis data structures and commands. To simplify working with Redis data structures in Python applications, Redis OM allows us to map Redis data to Python objects, offering a more intuitive, object-oriented approach to data management.

In the Java programming language, Jedis is a popular client library that enables developers to work seamlessly with Redis data structures. With Redis OM for Java, developers can further enhance their experience by mapping Java objects to Redis data structures, improving code organization and maintainability.

For JavaScript, we discussed node-redis, a widely used Redis client library designed to work efficiently with Node.js, offering a straightforward...