APIs are essential in app development. They allow software systems to communicate with each other, making it possible to pull in data from different sources or interact with other apps seamlessly. When it comes to API design, the choice always comes down to GraphQL versus REST. 

‍

Choosing the right type of API can make a big difference in how your app performs and scales. Two popular options are REST and GraphQL. Both have their own strengths and are used by developers around the world. However, they work differently, each with specific use cases where it shines. 

‍

This post will break down the key differences between GraphQL and REST. By the end, you’ll have a clearer idea of which one is the best fit for your project. 

‍

What Is REST?

REST (Representational State Transfer) is a widely used architectural style for APIs. It revolves around resources, each represented by a unique URL, and uses HTTP methods for operations. 

How REST Works

REST APIs follow a set of guidelines to keep things simple and consistent. Here are the main principles: 

• Resource-based URLs: Each piece of data is treated as a resource with its own URL. Here's an example: 

GET /users       # Gets a list of users

GET /users/1     # Gets details for a specific user with ID 1

POST /users      # Creates a new user

• HTTP methods: REST uses standard HTTP methods to interact with resources. Here are some of the common HTTP methods and what they do: some text
  • GET retrieves data
  • POST creates new data
  • PUT updates existing data
  • DELETE removes data Here’s how this might look in a simple REST API for managing books: 

GET /books            # Retrieves a list of books

GET /books/123        # Retrieves details of book with ID 123

POST /books           # Adds a new book

PUT /books/123        # Updates book with ID 123

DELETE /books/123     # Deletes book with ID 123

• Statelessness: REST APIs are stateless, meaning each request from a client contains all the information needed to process the request. The server doesn’t store any information about the client’s previous requests. This makes REST APIs simpler and more scalable.
• JSON responses: REST APIs typically return data in JSON format. It's easy to read and commonly used in web applications.

REST is great for applications where you need a predictable and easy-to-use structure. Its simplicity and reliance on HTTP make REST accessible to most developers. However, REST can sometimes lead to data over-fetching or under-fetching. This is where GraphQL may offer an advantage. 

What Is GraphQL?

GraphQL, developed by Meta, is a query language for APIs. Unlike REST, which relies on multiple endpoints, GraphQL allows clients to request only the data they need from a single endpoint. This flexibility makes it especially useful for applications with complex data requirements or multiple front-end clients. 

How GraphQL Works

GraphQL has a unique approach to handling data, based on a few key features: 

• Schema-based design: The server has a schema that defines the data types and relationships in the API. This schema acts like a contract between the server and the client. So, both know exactly what data is available and how it’s structured.
• Single endpoint: GraphQL uses a single endpoint to handle all requests. This endpoint usually looks something like this: 

‍

POST /graphql

‍

With a single endpoint, clients can request various data structures within one query, reducing the number of requests to the server.

• Flexible data structure: In GraphQL, clients can specify exactly what data they need, which prevents over-fetching or under-fetching.
• Real-time data with subscriptions: GraphQL also supports real-time updates using subscriptions. With subscriptions, clients can stay updated with live data changes. This feature is especially useful in apps that need real-time data, like chat applications or live dashboards.

In short, GraphQL is highly flexible and efficient, making it a great choice for applications where data requirements vary widely or change often. However, its setup can be more complex than REST, and it may require additional considerations for caching and performance. 

‍

GraphQL vs. REST: Example

Let’s look at an example where we want to retrieve a user’s profile along with their posts. This example will show how we request the same data differently in REST and GraphQL, highlighting the unique structure and flexibility each approach offers. 

‍

We want to get the following data: 

• user’s id, name, and email
• titles of the user’s posts

REST Example

As mentioned earlier, in REST, each resource typically has its own endpoint. So, we need multiple requests to gather the data. Here’s how it would work: 

‍

Request 1: To retrieve details of a user with the ID 1, you send the following request: 

GET /users/1

‍

The server responds with the user's details in a predefined structure: 

{

  "id": 1,

  "name": "John Doe",

  "email": "johndoe@example.com"

}

‍

Request 2: Next, you need a separate request to fetch the posts authored by the same user: 

GET /users/1/posts

‍

The server provides the list of posts authored by the user in another predefined structure: 

[

  { "id": 101, "title": "Understanding REST APIs" },

  { "id": 102, "title": "Getting Started with GraphQL" }

]

‍

Below are the key takeaways of the REST approach: 

• Multiple requests: Two separate requests are needed to retrieve the user's details and their associated posts.
• Fixed data structure: Each endpoint returns a predefined data structure. Clients can’t request just specific fields within each resource.

GraphQL Example

In contrast, GraphQL allows clients to request related data in a single query. By specifying the fields needed, clients can reduce over-fetching and under-fetching. Here’s an example: 

GraphQL query: This query fetches both user information and their posts in one request. The client specifies the exact fields to retrieve the desired information: 

query {

  user(id: "1") {

    id

    name

    email

    posts {

      title

    }

  }

}

‍

The server returns only the requested fields, neatly organized in the response: 

{

  "data": {

    "user": {

      "id": 1,

      "name": "John Doe",

      "email": "johndoe@example.com",

      "posts": [

        { "title": "Understanding REST APIs" },

        { "title": "Getting Started with GraphQL" }

      ]

    }

  }

}

‍

The GraphQL approach stands out here because of the following reasons: 

• Single request: Only one request is required to retrieve both user and post data.
• Customizable data: The client specifies which fields to return, so only relevant data is fetched, reducing unnecessary data transfer.

This example highlights how GraphQL’s structure can streamline data requests, especially in applications where clients need various fields from multiple related resources. 

GraphQL vs. REST: Comparison

Choosing between GraphQL and REST often comes down to understanding the strengths of each approach. Here, we’ll compare them across three critical dimensions: features, architecture, and performance. 

Features

• REST’s predictable structure: REST APIs are resource-based, with fixed endpoints that return a standard response structure. It’s easy to use for simple apps. However, they can suffer from over-fetching (getting more data than needed) or under-fetching (missing data) due to rigid structures.
• GraphQL’s flexible, client-driven querying: GraphQL provides flexible, client-driven querying. Clients can request only the data they need from a single endpoint, reducing over-fetching and under-fetching. This is ideal for complex data relationships, though it places the responsibility for efficient queries on the client.

Architecture

• REST’s multi-endpoint structure: REST uses multiple endpoints for different resources. While straightforward, this leads to fragmented requests when related data is needed, causing inefficiencies in fetching complex data.
• GraphQL’s single endpoint and schema approach: GraphQL has a single endpoint and uses a schema to define available data and its relationships. This simplifies fetching complex, nested data in one request. However, schema updates need careful planning to ensure compatibility.

Performance

• REST’s HTTP caching benefits: REST supports HTTP caching for GET requests, improving response times and reducing server load by caching resources at the endpoint level. However, it can't cache multiple related resources together. For example, if the /users/1 endpoint response is cached, any future requests for the same data can be served directly from the cache, significantly speeding up the response time. However, the multi-endpoint structure means that only specific resources are cached, so it doesn’t help if multiple related resources are requested together.
• GraphQL’s tailored responses and potential over-fetching/under-fetching: GraphQL avoids over-fetching by allowing clients to specify exactly what data they need. However, it lacks built-in HTTP caching due to its single endpoint. You'll need to implement custom caching solutions for optimal performance, especially in high-traffic scenarios.

GraphQL vs. REST: Pros and Cons

Both REST and GraphQL have distinct strengths and limitations that make them suitable for different use cases. Here, we’ll break down the primary pros and cons of each approach to help developers better understand the benefits and tradeoffs. 

Pros of REST and GraphQL

The table below highlights the advantages of REST and GraphQL, offering insight into why one might choose a specific approach:

Cons of REST and GraphQL

The table below outlines the potential challenges associated with REST and GraphQL:

When to Use GraphQL vs. REST

The Postman's State of the APIs report shows that 90% of developers use REST APIs. However, GraphQL has also quickly become popular and has already surpassed SOAP.

‍

‍

Choosing between GraphQL and REST depends on the specific needs of your project, the data complexity, and the resources available for implementation. Let’s look at some scenarios where each API type shines. 

When to Use REST

This section focuses on the scenarios where REST APIs are most effective. REST's straightforward, resource-based approach makes it a popular choice for many applications, especially those with simple data structures and requirements. 

• Simple or CRUD-based applications: REST’s straightforward, resource-based approach is ideal for simpler applications where data relationships aren’t deeply nested. It’s a great fit for CRUD-based systems like content management or inventory tracking, where basic resource management is the primary goal.
• Benefits from HTTP caching: REST is especially effective when caching is critical to reduce server load. Its use of standard HTTP methods like GET for caching can improve response times and reduce redundant requests for static data.
• Broad support and quick testing: With REST’s widespread adoption, you’ll find a range of resources and tools for rapid testing and debugging. REST also integrates smoothly with tools like Postman and popular backend frameworks, making it easier to get started quickly.

For more insights into REST’s use cases and how to integrate REST APIs into your projects, check out Neurelo and their REST API resources. 

When to Use GraphQL

GraphQL's flexibility and efficiency make it ideal for applications with complex data requirements and varying client needs. It might be the better choice if the following are true of your project. 

• Complex, nested data requirements: If your project has deeply nested relationships, such as user profiles linked with multiple data types or interconnected data across various domains, GraphQL’s flexible querying structure provides efficiency by allowing clients to retrieve related data in a single request.
• Optimized data usage: For applications that need to minimize payload sizes (like mobile or IoT devices), GraphQL’s ability to tailor responses ensures that clients receive only the data they need. This reduces bandwidth usage and speeds up response times, which is essential in mobile-first applications.
• Dynamic data requirements across clients: If your application has multiple front-end clients (e.g., web, mobile, or different platforms) with varying data needs, GraphQL can streamline the process by allowing each client to customize its requests without changing the server.

Learn more about getting started with GraphQL and try out Neurelo's GraphQL resources to see how they could fit into your projects. 

‍

Conclusion

Choosing between GraphQL and REST ultimately depends on your project’s unique needs. If you value simplicity, broad compatibility, and ease of caching, REST might be your go-to choice. On the other hand, if flexibility, precise data retrieval, and a modern client-driven approach are your priorities, GraphQL could be the perfect fit. 

‍

Remember, it’s not about one being better than the other—it’s about understanding their strengths and aligning them with your goals. Experiment with both approaches and decide based on the specific challenges you aim to solve. 

‍This post was written by Ashutosh Krishna. Ashutosh is an Application Developer at Thoughtworks. He enjoys creating things that live on the internet. He is passionate about full-stack development and DevOps. In his free time, he enjoys sharing his technical knowledge with others through articles and tutorials.