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How to Optimize GraphQL Performance with Redis


GraphQL is a great way to build backend applications. It simplifies the project’s structure and scales easily, but there are some challenges that come with it. One of the biggest is how to optimize GraphQL at scale. In this post, we will show you how to use Redis as an optimization tool for your GraphQL servers.

What is Redis?

Redis is an open-source database that can be used with any programming language. It is well-suited for large-scale applications. It’s a key-value store that can be used to store and retrieve data. It is designed to be fast, with no single point of failure. It also provides a high degree of concurrency, which means it's possible for multiple clients to access the same data at the same time. Redis is also lightweight enough that you can run it in the cloud.

Why GraphQL?

GraphQL is a query language for APIs and a runtime for fulfilling those queries with your existing data. GraphQL provides a complete and understandable description of the data in your API, gives clients the power to ask for exactly what they need and nothing more, makes it easier to evolve APIs over time, and enables powerful developer tools.

Why Redis with GraphQL?

Redis can be your best friend when it comes to optimizing the performance of GraphQL. First, Redis provides a powerful system that helps you to cache queries and results so that they can be reused. This is crucial because there's no way to predict how often you'll need to run a query on a serverless architecture. Sometimes you use a 3rd party API that is slow, or there are request limits, or even the local databases could take a quite long time to return the data. If you're creating tons of different queries every day, this can add up quickly!

Different caching strategies

There are two main caching strategies that you can use with GraphQL and Apollo Server:

1. Caching the entire response (use Redis as a cache)

Caching the whole response is the most straightforward way to cache your GraphQL queries. When you cache the entire response, you're essentially caching the entire query, including all of the fields that are returned by the query. This is a great option if you're only interested in caching the data that are returned by the query, and you don't need to worry about caching any of the other data that is returned by the query, or if you have a repeatable query for different users.

Example of in-memory cache:

2. Caching individual fields (use Redis as a data store)

This is a more proper way to cache your GraphQL queries. It's also a more complex way to cache queries in Apollo Server. When you cache individual fields, you're caching the individual fields that are returned by the query. This is a great option if you're only interested in caching the data that are returned by the query, and you don't need to worry about caching any of the other data that are returned by the query.

What not to cache?

Redis is not built for large data. If you're storing critical business data, you're going to need a more traditional data solution.

If you're looking for a way to store complex data queries, look elsewhere. Redis is designed to be simple and fast, but that doesn't mean it's ready for just about anything. Even if you think your data could grow into a large enough set that it would benefit from relational databases, remember that Redis does not have support for building relational databases from scratch. It has no support for tables or relationships or any other kind of constraints that would be required if your data was stored in a relational database.


In this post, we showed you how to use Redis as an optimization tool for your GraphQL. We also showed you how to use Redis as a cache and as a data store. We hope you found this post helpful! Also, check out our GraphQL Serverless Contentful starter kit on If you have any questions or comments, please feel free to send them to us by email at Thanks for reading!

This Dot Labs is a development consultancy that is trusted by top industry companies, including Stripe, Xero, Wikimedia, Docusign, and Twilio. This Dot takes a hands-on approach by providing tailored development strategies to help you approach your most pressing challenges with clarity and confidence. Whether it's bridging the gap between business and technology or modernizing legacy systems, you’ll find a breadth of experience and knowledge you need. Check out how This Dot Labs can empower your tech journey.

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How to Resolve Nested Queries in Apollo Server cover image

How to Resolve Nested Queries in Apollo Server

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