GraphQL vs. REST API: Understanding the Differences

Published on: February 22, 2023
LicenseSpring Guide
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In recent years, GraphQL has been seen as an interesting alternative to traditional REST APIs for building web and mobile applications. GraphQL and REST both provide ways for clients to communicate with servers, but they differ in some important ways. Let's explore some of the differences between GraphQL and REST, and discuss the benefits of each approach. We'll also discuss the situations in which each technology is best suited and provide guidance on when to use GraphQL or REST for your project.

What is an API, anyway?

An API stands for `Application Programming Interface`. It is a set of protocols, routines, and tools that specifies how different software components should interact with each other. In simpler terms, an API is a way for different software systems to communicate with each other.

What Is an API Used For?

APIs allow developers to create software that can interact with other applications or services, without having to understand or modify the underlying code. This makes it possible to build more complex software systems that leverage the functionality of other systems, without having to reinvent the wheel each time.

What Is GraphQL?

GraphQL is an open-source query language and runtime for building APIs. It was initially developed by Meta (called Facebook at the time). It allows clients to specify the exact data they need from a server and receive only that data, rather than receiving a predetermined set of data in a RESTful API.

With GraphQL, clients send queries to the server, which returns a JSON response that matches the structure of the query. This approach provides more flexibility and efficiency compared to traditional REST APIs, as it reduces over-fetching and under-fetching of data.

GraphQL also provides a strongly typed schema that defines the types and fields available in the API, allowing clients to validate queries at the compile time. This improves the developer experience and reduces the likelihood of runtime errors.

What Is REST?

REST, or Representational State Transfer, is an architectural style for building APIs that is widely used on the web. A REST API exposes a set of resources and operations that can be accessed over the internet using HTTP, such as GET, POST, PUT, and DELETE.

In a REST API, clients interact with the server by sending HTTP requests to URLs that represent resources, such as /users or /products. The server responds with a representation of the resource in a standardized format, such as JSON or XML.

One of the key principles of REST is that resources should be stateless, meaning that each request should contain all the information necessary to complete the request. This allows servers to scale easily and clients to make requests in any order.

What Are the Differences Between GraphQL and REST?

There are several key differences between REST and GraphQL, including:

  1. Data retrieval: REST APIs typically have a fixed set of endpoints that return predetermined data structures. With GraphQL, clients can request specific data fields and the server responds with only the requested data, which can lead to more efficient data retrieval.
  2. Request structure: In REST, clients must make multiple requests to retrieve related data from different endpoints, while in GraphQL, clients can request related data in a single request, reducing the number of requests and improving performance.
  3. Schema and type system: GraphQL uses a strongly-typed schema to define the types and fields available in the API, which can be used to validate queries at the compile time. REST APIs do not typically have a schema or type system.
  4. Caching: REST APIs are more easily cacheable, as each resource has a unique URL, while GraphQL APIs require a more complex caching strategy, as queries can be constructed dynamically.
  5. Tooling: GraphQL has a wide range of tooling and libraries available to simplify API development and testing, while REST has been around for longer and has a more established set of tools.

Overall, GraphQL provides a more flexible and efficient approach to data retrieval, while REST provides a simpler and more standardized approach. The choice between the two will depend on the specific requirements of a project and the preferences of the development team.

When to Choose GraphQL or REST:

Here is a general rule of thumb:

Choose REST when:

  • The data model is simple and does not require complex queries
  • The API is heavily cacheable, as REST APIs are more easily cacheable
  • You need a simple and standardized approach to API development
  • Your team is more experienced with REST or the project's technology stack is better suited for REST

Choose GraphQL when:

  • The data model is complex and requires complex queries
  • The API needs to support dynamic queries, as GraphQL allows you to specify the exact data you need
  • You need a more flexible and efficient approach to API development
  • You want to take advantage of GraphQL's strongly-typed schema and validation features
  • You need a more modern and developer-friendly approach to API development

What Are Some of the Top Frameworks and Libraries to Use Within GraphQL?

  1. Apollo Server: Apollo Server is a GraphQL server that provides a set of tools and services for building and deploying GraphQL APIs. It supports a range of data sources, including SQL databases, NoSQL databases, and REST APIs, and provides a set of powerful features for caching, error handling, and testing.
  2. GraphQL Yoga: GraphQL Yoga is a fully-featured GraphQL server that is built on top of the Express web framework. It provides a simple and flexible way to build GraphQL APIs, and includes features such as file uploads, real-time subscriptions, and built-in support for authentication and permissions.
  3. Prisma: Prisma is an open-source database toolkit that provides a set of tools for building GraphQL APIs. It includes a powerful data modeling tool, a database client, and a set of utilities for generating a GraphQL schema from a database schema.
  4. GraphQL Nexus: GraphQL Nexus is a code-first GraphQL schema construction framework that allows developers to define a GraphQL schema in code using a fluent and type-safe API. It provides a set of features for building modular and scalable GraphQL APIs, and supports TypeScript and JavaScript.

What Are the General Steps to Follow When Building a GraphQL API?

  1. Define your data model: The first step in building a GraphQL API is to define your data model. This involves identifying the types of data you want to expose through your API, and how they are related to each other. You can use a tool like GraphQL schema language to define your data model.
  2. Design your API schema: Once you have defined your data model, the next step is to design your API schema. This involves defining the queries, mutations, and subscriptions that will be available to clients, as well as the types and fields that they will return.
  3. Implement your resolvers: Resolvers are functions that are responsible for fetching the data for each field in your API schema. You will need to implement your resolvers to retrieve the data from your data sources and return it in the correct format.
  4. Configure your server: Once you have implemented your resolvers, the next step is to configure your GraphQL server. This involves choosing a server framework, configuring your resolvers and schema, and setting up any middleware or other services that your API depends on.
  5. Test and document your API: Finally, you will need to test your API to ensure that it is working correctly, and document it so that clients can understand how to use it. You may also want to provide tools or libraries to help clients interact with your API more easily.

What Are Some of the Most Popular Frameworks to Build a Rest API?

  1. Express: Express is a lightweight and flexible framework for building web applications and APIs in Node.js. It provides a simple and intuitive API for defining routes, handling middleware, and serving static files, and is widely used for building REST APIs.
  2. Django REST framework: Django REST framework is a powerful and flexible toolkit for building RESTful web APIs in Python. It provides a set of tools and utilities for building APIs, including serializers, views, and authentication.
  3. Spring Boot: Spring Boot is a popular Java framework for building web applications and APIs. It provides a set of tools and libraries for building RESTful APIs, including Spring MVC, Spring Data, and Spring Security.
  4. Flask: Flask is a lightweight and flexible web framework for Python. It provides a simple and expressive API for building web applications and APIs, and is widely used for building REST APIs.
  5. Ruby on Rails: Ruby on Rails is a popular web application framework for building web applications and APIs in Ruby. It provides a set of tools and libraries for building RESTful APIs, including Rails Controllers, Active Model Serializers, and Rails Routing.

What Are the General Steps You Would Follow When Building a Rest API?

  1. Identify the resources: The first step in building a REST API is to identify the resources that will be exposed through the API. These could be entities such as users, products, or orders, or they could be more abstract concepts such as search results or analytics data.
  2. Define the endpoints: Once you have identified the resources, you need to define the endpoints that will be used to access them. Each endpoint should correspond to a specific operation on the resource, such as GET, POST, PUT, or DELETE.
  3. Design the data model: The data model is the structure of the data that will be exposed through the API. You'll need to define the attributes of each resource, the relationships between resources, and the data types used for each attribute.
  4. Implement the API: Once you have defined the endpoints and data model, you can start implementing the API. You'll need to write code to handle requests and responses, and to map the requests to the corresponding operations on the data model.
  5. Test the API: Once you have implemented the API, you should test it to make sure it works as expected. You can use tools like Postman or curl to test the API, or you can write automated tests using a testing framework.
  6. Optimize performance: Finally, you should optimize the performance of the API. This may involve implementing caching, pagination, or other performance optimizations, depending on the specific requirements of the project.

Other Popular Alternatives:

There are several other alternatives to GraphQL and REST that are gaining popularity in the world of web APIs. Some of them are:

  1. gRPC: gRPC is a modern, high-performance framework for building APIs. It uses Protocol Buffers as the data interchange format and supports multiple programming languages. gRPC also provides features like bi-directional streaming and flow control, making it a good option for building real-time applications.
  2. Falcor: Falcor is a JavaScript library for building efficient data-driven applications. It uses a JSON-like data model that allows clients to specify the data they need and reduces the number of roundtrips between the client and server. It was developed by Netflix.
  3. JSON API: JSON API is a specification for building APIs that use JSON as the data format. It defines a standard set of rules for querying, filtering, sorting, and paginating data, making it easier to build consistent APIs.
  4. OData: OData is a protocol for building and consuming RESTful APIs. It uses a standardized set of query parameters to enable filtering, sorting, and paging of data, and supports multiple data formats, including JSON and XML.
  5. REST Hooks: REST Hooks is a pattern for building real-time APIs. It allows clients to subscribe to changes in a resource and receive notifications when the resource changes, rather than having to poll the API for updates.
Kyle Brandon
Kyle BrandonSystems Engineer - LicenseSpring Software
Kyle Brandon is a Systems Engineer at LicenseSpring Software, based out of Vancouver, Canada. With over two years experience, Kyle helps current and prospective customers with ensuring successful implementation of all LicenseSpring has to offer. Specializing in Computing Science, Kyle uses that experience to assist with troubleshooting user-reported bugs and provide helpful guides.