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GraphQL vs REST comparison: choosing the right API

João Inez

February 21, 2024

Min Read
GraphQL vs REST comparison: choosing the right API

What is GraphQL?

GraphQL is a query language for APIs that enables declarative data fetching in order to give the client the power to specify exactly the data that is needed from the API. It makes easier to evolve APIs over time.

Now that we know what GraphQL is, I want to clarify what it is not, as I feel that there is still some confusion about it.

Firstly, it does not have anything to do with databases. It is not an alternative to SQL or a brand new ORM.

Secondly, it is not a REST replacement, but an alternative. You don't have to pick between one and the other, they can happily co-exist in the same project.

Last but not least, GraphQL is not complicated or scary. It is quite easy to understand its declarative nature and exactly how it is possible to take the best from it.

Who created GraphQL

GraphQL was developed internally by Facebook in 2012 before being open-sourced in 2015, with its stable version released just in June 2018. On 7 November 2018, the GraphQL project was moved from Facebook to the newly-established GraphQL Foundation, hosted by the non-profit Linux Foundation.

Lee Byron, GraphQL's creator, aims to make GraphQL omnipresent across web platforms.

Which companies use GraphQL

GraphQL is being used by teams off all sizes, in many different environments and languages. The main companies that are using GraphQL are Facebook, Github, Pinterest and Shopify.

GraphQL in context

Before moving on to the comparison with REST, I will go through a simple GraphQL query where we can fetch a user as well as his or her name and age:


And the JSON response we will get from it:


As I stated previously, GraphQL's declarative nature makes it incredibly easy to understand what is going on at all times, as we are basically writing JSON objects without the values.

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What is REST?

REST was defined by Roy Fielding, a computer scientist that presented the REST principles in his PhD dissertation in 2000.

REST (Representational State Transfer) is a software architectural style that defines a set of constraints which make any web service – a true RESTful API. The REST constraints are:

Client-server architecture

Client-server architecture means that the user-interface concerns should be separated from the data storage concerns to improve the user interfaces portability across multiple platforms.

Client-Server Architecture | REST

Stateless

A stateless server does not persist any information about the user who uses the API. This means that the server does not remember if the user is sending is first request or not.

Client-Stateless-Server | REST

Cacheability

REST API responses must define themselves as cachable or non-cachable to prevent clients from providing any inappropriate data that can be used on future requests.

Layered system

A Layered system means that if a proxy or load balancer is placed between client and server, the connections between them should not be affected, and the client did not know if is connected to the end server or not.

Uniform interface

A Uniform interface suggests that it should be a uniform way of interacting with a given server despite the device or application type (website, mobile app). The main guideline is that each resource has to be identified on requests.

REST Architectural Style

Considering all REST constrains, the following image demonstrates REST architectural style:

REST Architectural Style
Source: Developing Social Networks Mashups: An Overview of REST-Based APIs | Procedia Technology
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Why was GraphQL created if there's already REST

There are two main reasons why companies such as Facebook, Netflix and Coursera started developing alternatives to REST:

1. In the early 2010s, there was a boom in mobile usage, which led to some issues with low-powered devices and sloppy networks. REST isn't optimal to deal with those problems;

2. As mobile usage increased, so did the number of different front-end frameworks and platforms that run client applications. Given REST's inflexibility, it was harder to develop a single API that could fit the requirements of every client.

If we go even further, we realize that the main reason why an alternative solution was identified was because most of the data used in modern web and mobile applications has a graph shape. For instance, news pieces have comments, and those comments may have features such as likes or spam flags, which are created or reported by users. This example describes how a graph looks like.

Consequently, Facebook started developing GraphQL. Simultaneously, Netflix and Coursera were also working on alternatives themselves. After Facebook open-sourced GraphQL, Coursera dropped their efforts and adopted the new tech. Netflix, however, continued developing their own REST alternative and later open sourced Falcor.

GraphQL Architecture

In the next sections, I will explain why GraphQL allows for more flexibility than REST, but first, let's look at its architecture.

GraphQL Architecture
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Is GraphQL better than REST?

Is GraphQL better than REST? GraphQL provides a query language that allows clients to request only the data they need and enables real-time updates. REST relies on rigid endpoints and data structures. Whether GraphQL is "better" depends on the specific requirements and flexibility needed in an API-driven project.

In this section I will go point by point through a practical example, comparing REST to GraphQL in order to demonstrate the flexibility of Facebook's query language.

Imagine that you have a blog, and you want the front page to show all the latest posts. In order to achieve this, you need to fetch the posts, so you will probably do something like this:

GET /api/posts


But what if you want to see the author as well? You have three options to achieve this:

  • Fetch the authors from another resource:


  • Modify the resource to also return the author:


  • Create a resource that returns the posts with the author:


Each of these approaches will create a problem of its own, so let's have a look at them one by one to see how GraphQL is able to solve the following problems.

Under-fetching

With the first approach – fetching the authors from another resource – you will end up with two server requests instead of one, and as you continue to scale, you may have even more requests to different endpoints in order to fetch all the needed data.

With GraphQL, this would not happen. You would only have one request, and you would not have to make multiple round trips to the server, as seen below:


Over-fetching

Looking at the second approach – modifying the resource to also return the author – you can see that it solved the problem pretty nicely. However, changing a resource may have a secondary effect elsewhere on your application. More precisely, over-fetching.

Let's go back to your blog, but this time you also have a sidebar showing off the top monthly posts with their titles, subtitles and date, that is using the resource /api/posts. Since you modified the resource, now it also shows the author with it. However, we don't need it for the sidebar.

While this may not look like a problem, for users on limited data plans, having a website fetch useless data is not ideal. Since GraphQL allows the client to only fetch the needed data, this problem would not exist:


Slow front-end development

Lastly, let's have a look at the last approach – creating a resource that returns the posts with the author – since it is a common pattern to structure the endpoints according to the views in your project.

While this may solve problems such as the one described above, it also slows down the front-end development, since each specific view needs its specific endpoint. If at any point a view needs new data, the development has to slow down until the endpoint is updated.

Again, since GraphQL gives power to the client to fetch the needed data only, nothing slows down, as it's very simple to just add a new field.

You would get from this:


To this:


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GraphQL and REST comparison

Differences

Let's just do a quick recap regarding the differences between REST and GraphQL:

  • GraphQL is a language and a set of tools that use HTTP to work on single endpoints in order to optimize flexibility and performance.
  • In GraphQL, data is organized into a graph, and objects are structured by nodes following a schema.
  • REST is an architectural concept for network-based software that has typically been used to develop new APIs.
  • GraphQL solves both over-fetching and under-fetching issues by allowing the client to request only the needed data;
  • Since the client now has more freedom in the fetched data, development is much faster with GraphQL than what it would be with REST.
  • In GraphQL, the identity of an object is separated from how a developer fetches it. In REST, the endpoint is the identity of an object.
  • In GraphQL, the server determines the available resources by allowing the client to request the needed data at a specific time. In REST, the resources' size is defined by the server.
  • In GraphQL, a single query can call various resolvers to provide a response with multiple resources. In REST, one query usually calls one route handler function.
  • Since GraphQL follows the relationships defined in the schema, it is possible to transverse from the entry point to the related data with a single request. Contrarily, REST requires calling several endpoints to fetch related resources.

Similarities

As previously mentioned, GraphQL does not replace REST. Despite their differences, GraphQL and REST also have similarities:

  • They can both be fetched by an HTTP GETrequest with a URL and return the request in JSON data.
  • GraphQL and REST allow the specification of IDs for resources.
  • Both GraphQL (fields) and REST (endpoints) call functions on the server.
  • They both have entry points into the data. In GraphQL API, the list of fields (considering both the Mutationand the Query types) is identical to the list of endpoints in a REST API.
  • GraphQL and REST are able to distinguish when an API is intended to write or to read data.
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What is GraphQL good for

Nowadays, almost every business aims to build mobile cross-platform applications because the customer interaction with the product increases significantly if they are able to access it via their phones. When you use a mobile app, you expect them to be responsive and with low latency.

By using GraphQL you will be able to achieve these goals in a really easy way. It helps the client to fetch the amount of data needed to render a specific view.

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What is REST good for

Until now, I imagine that we share the same opinion that GraphQL is awesome, but that's not entirely true. There are still some missing elements to make it perfect. If you aim to have one of the next points in your project, you should consider the usage of REST.

Non-existent HTTP caching mechanism

Nowadays, every browser provides an implementation of an HTTP cache to easily avoid refetching resources and to identify if two resources are the same.

When using GraphQL there is no way to get a globally unique identifier for a given object because we use the same URL for all the requests. To have cache on GraphQL you have to setup your own cache.

Monitoring and Error Reporting

When using REST you can build a monitoring system based on API responses. On GraphQL you don't have that, because it always return 200 OK status response. A typical GraphQL error looks like this:


Looking on this response you can see that is very difficult to handle and monitoring different error scenarios.

Resource Attacks

As you now know, with GraphQL you can query exactly what you want whenever you want, but we should be aware that this leads to complex security implications. If a malicious actor tries to submit an expensive nested query to overload your server or database and your server does not have the right protections, you will be vulnerable to DDoS (Denial-of-service attack) attacks.

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GraphQL's features overview

Now that we know how it stacks up against REST, let's talk about some of the features that are unique to GraphQL.

Schema and Type System

GraphQL uses its own type system to define the schema of an API, with its syntax called Schema Definition Language (SDL). The schema serves as a contract between the server and the client to define how a client can access the data.

Once the schema is defined, the front-end and back-end teams can work independently, as the front-end can be easily tested with mock data. The front-end can also get useful information from the schema, such as its types, queries and mutations using GraphiQL or introspection. The GraphQL's schema also provides type safety, which is a plus for the front-end and back-end development, as it catches type errors early.

A schema example:

GraphQL IDE

GraphQL IDE is one of the most useful features of GraphQL development. It takes advantage of its self-documenting nature to make development a breeze.

Using GraphiQL or GraphQL Playground, you can just inspect your schema and even run queries and mutations to test out your API.

GraphQL Playground

Wrap up

GraphQL provides a smooth and fast development environment with its declarative and flexible nature, offering many improvements over REST.

It already has a large community and a vibrant ecosystem, and was already implemented in several popular languages, such as JavaScript, Go and Java.

While this post only dipped the toes into the ocean that is GraphQL, its website has a plethora of information and is an amazing place to learn and start using GraphQL.

If you are aiming to develop an API to be used on a mobile application you should have GraphQL as first option because bandwidth usage matters. If your application requires a robust API, with caching and a monitoring system you should go with REST.

With all this being said, it's not a perfect technology, and it still has a couple of drawbacks when compared with REST. But considering how young it is, the future looks incredibly bright for GraphQL.

Join us and find out about our exciting projects!

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João Inez
João Inez

Web developer, commonly found typing null instead of nil. Love exploring the functional style of Javascript.

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