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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
6
Part 2: Data Modeling
11
Part 3: From Development to Production

Interacting with data

Interacting with your data efficiently is enabled by the workbench feature in RedisInsight. The workbench section, represented by the second icon on the vertical panel on the left side, refers to a section of the tool where you can interact with its Redis databases. It allows you to write and execute Redis commands, query data, view results, and generally interact with your data.

For example, you could run aggregation queries, visualize time-series data as charts, or even zoom in to specific parts of a chart (to revert to the original view after zooming, simply double-click anywhere on the chart).

A useful interactive feature of this chart allows you to zoom in to any specific section of the data. This can be achieved by dragging your cursor over the desired section of the chart, demonstrated as follows:

Figure 10.8 – RedisInsight Time Series chart zoom interaction

Figure 10.8 – RedisInsight Time Series chart zoom interaction

The chart representation isn’t limited to a single...

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