Book Image

Mastering Redis

By : Vidyasagar N V, Jeremy Nelson
Book Image

Mastering Redis

By: Vidyasagar N V, Jeremy Nelson

Overview of this book

Redis is the most popular, open-source, key value data structure server that provides a wide range of capabilities on which multiple platforms can be be built. Its fast and flexible data structures give your existing applications an edge in the development environment. This book is a practical guide which aims to help you deep dive into the world of Redis data structure to exploit its excellent features. We start our journey by understanding the need of Redis in brief, followed by an explanation of Advanced key management. Next, you will learn about design patterns, best practices for using Redis in DevOps environment and Docker containerization paradigm in detail. After this, you will understand the concept of scaling with Redis cluster and Redis Sentinel , followed by a through explanation of incorporating Redis with NoSQL technologies such as Elasticsearch and MongoDB. At the end of this section, you will be able to develop competent applications using these technologies. You will then explore the message queuing and task management features of Redis and will be able to implement them in your applications. Finally, you will learn how Redis can be used to build real-time data analytic dashboards, for different disparate data streams.
Table of Contents (18 chapters)
Mastering Redis
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Summary


This chapter started with a survey of data storage technologies, starting with the most popular, a relational database system supporting SQL. From the relational databases, we examined document datastores focusing on MongoDB with BSON documents. Following document datastores, graph databases were briefly examined finishing with full-text search and key-value data-storage, highlighting Redis. We finished the survey by examining wide column datastores.

Four detailed examples of using Redis as a complement were demonstrated with an experiment using MongoDB to store usage data verses Redis and the performance and reduction in complexity of the application using Redis for analytics in a hypothetical MARC21 catalog. The second example explored using Redis as preprocessor for deduplicating BIBFRAME RDF graphs using the Linked Data Fragments Server as a transitory datastore. The third example showed Redis and the Linked Data Fragments Server complement the Graph Linked Data Platform combination...