From REST to GraphQL: Why and How I Made the Switch

As a software engineer with 4+ years of experience building REST APIs, I’ve always appreciated the simplicity and reliability REST brings to the table. Whether it was designing endpoints or structuring responses, REST was my go-to solution.

But earlier this year, everything changed. I was tasked with jumping onto a project that required handling large, complex, and interrelated data sources. This wasn’t just about fetching a list of users or updating a single record, it demanded flexibility, precision, and efficiency at a scale that REST struggled to provide.

Enter GraphQL. 📌

At first, I was skeptical. Why fix something that isn’t broken? But as I delved deeper, GraphQL didn’t just meet the project’s needs—it redefined how I thought about APIs. With its ability to:

• Return data in a flexible structure defined by the client,
• Operate through a single URL endpoint,
• Reject invalid requests based on a strongly-typed schema, and
• Deliver data in predetermined, mutually understood formats,

GraphQL quickly became more than a solution—it became my new standard for API design.

That said, the aim of this article is not to discredit REST APIs in favor of GraphQL. In fact, I believe the two can complement each other beautifully. REST still plays a crucial role in my projects, especially for specific use cases where a dedicated REST endpoint is more practical than a GraphQL query.

In this article, I’ll share:

1. Why I made the switch from REST to GraphQL,
2. The benefits I’ve experienced firsthand, and
3. A simple guide to help you build your very first GraphQL server.

Whether you’re a beginner curious about GraphQL or an experienced engineer looking to transition, this article will show you why GraphQL is worth your attention and how it can transform your projects without replacing REST entirely.

My Journey from REST to GraphQL

For years, REST APIs were my bread and butter. I relied on them to build robust systems, manage data, and deliver functionality. But as my projects grew more complex, cracks started to show.

Challenges with REST APIs

One recurring frustration was over-fetching and under-fetching data. I’d either get too much information I didn’t need or have to make multiple requests to get everything I did. Managing numerous endpoints added to the complexity, making updates and maintenance a chore.

Discovering GraphQL

Earlier this year, I joined a project that needed to work with large, interconnected data sources. REST wasn’t cutting it, and the team suggested GraphQL. Initially, I was skeptical, but the promise of querying exactly what was needed from a single endpoint intrigued me.

First Impressions of GraphQL

Starting with GraphQL wasn’t without its challenges. Schemas and resolvers felt daunting, but the flexibility and control it offered made the effort worthwhile. Over time, I realized how seamlessly it addressed the pain points I faced with REST.

While I still use REST for specific cases, GraphQL has become my preferred tool for tackling complex and dynamic data requirements.

Why I Made the Switch

As I delved deeper into GraphQL, a few key advantages stood out, making the transition a no-brainer:

• Flexibility: With GraphQL, I could fetch exactly the data I needed—nothing more, nothing less. No more juggling multiple endpoints or dealing with over-fetching.
• Efficiency: A single query could replace multiple REST API calls, drastically improving performance. This was especially impactful in applications with complex, interrelated data.
• Developer Experience: The strongly-typed schema, introspection, and better debugging tools made development smoother and less error-prone.
• Ecosystem and Community Support: Tools like Apollo Client and GraphQL enriched the experience, making it easier to learn and integrate GraphQL into my workflow.

How I Made the Switch

The journey wasn’t without its challenges, but breaking it down into steps made the transition manageable:

Step 1: Understanding GraphQL Basics

I started by learning the core concepts:

• Queries to fetch data.
• Mutations to modify data.
• Resolvers to connect schema definitions to actual data sources.

This foundational understanding was key to building my first GraphQL server.

Step 2: Building My First GraphQL Server

To get hands-on, I built a simple server using Node.js and Apollo Server. The process looked like this:

1. Set up a Node.js project: Initialized the project with npm init and added essential dependencies.
2. Install GraphQL dependencies: Installed apollo-server and graphql.
3. Write a basic schema and resolver: Defined a schema to describe the data and wrote resolvers to fetch it.
4. Run the server: Fired it up and tested queries using GraphQL.

Seeing it work for the first time was exhilarating🎉 It made the effort feel worthwhile.

Step 3: Transitioning Existing REST APIs

The next step was integrating GraphQL into an existing REST-based project. I followed a gradual approach:

1. Identified key REST endpoints to replace with GraphQL queries or mutations.
2. Built corresponding GraphQL schemas and resolvers.
3. Maintained REST endpoints alongside GraphQL during the transition to ensure stability.

This hybrid approach allowed me to roll out GraphQL incrementally without disrupting existing functionality.

Quick Starter Guide: Build Your First GraphQL Server

Getting started with GraphQL is simpler than it seems. Here’s a quick guide to set up a basic server using Node.js and Apollo Server:

Step 1: Install Dependencies

Start by initializing a Node.js project and installing the necessary packages:

npm init -y  
npm install apollo-server graphql  

Step 2: Define a Schema and Resolver

Create a file called index.js and add the following code:

const { ApolloServer, gql } = require('apollo-server');  

// Simulated user data  
const users = [  
  { id: '1', name: 'John Doe', email: '[e-mail]' },  
  { id: '2', name: 'Jane Smith', email: '[e-mail]' },  
  { id: '3', name: 'Alice Johnson', email: '[e-mail]' },  
];  

// Define schema  
const typeDefs = gql`  
  type User {  
    id: ID  
    name: String  
    email: String  
  }  

  type Query {  
    users: [User]  
    user(id: ID!): User  
  }  
`;  

// Define resolvers  
const resolvers = {  
  Query: {  
    users: () => users,  
    user: (_, { id }) => users.find((user) => user.id === id),  
  },  
};  

// Create server  
const server = new ApolloServer({ typeDefs, resolvers });  

// Start server  
server.listen().then(({ url }) => {  
  console.log(`🚀 Server ready at ${url}`);  
});  

Step 3: Run the Server and Test

Start the server with:

node index.js  

Open the provided URL in your browser or a tool like GraphQL and test the queries:

Query All Users:

query {  
  users {  
    id  
    name  
    email  
  }  
}  

Query a Single User by ID:

query {  
  user(id: "1") {  
    name  
    email  
  }  
}  

Congratulations🎉🎉 You’ve just built your first GraphQL server!

Lessons Learned

Switching to GraphQL taught me invaluable lessons:

What Went Well

• The transition significantly improved data fetching efficiency. No more under-fetching or over-fetching!
• The strongly-typed schema reduced runtime errors and made debugging easier.
• The ecosystem's tooling (like Apollo Client) enhanced developer productivity.

What I’d Do Differently

• Learn Gradually: I dove in headfirst, which was overwhelming. Taking a phased approach and focusing first on queries and mutations would’ve been smoother.
• Start Small: I’d start by replacing a single REST endpoint with GraphQL to get a feel for the workflow.

Advice for Others

• Don’t Abandon REST Entirely: REST and GraphQL can coexist. Use REST for simple operations and GraphQL for complex, interrelated data needs.
• Leverage the Community: GraphQL has an active community and excellent resources. Don’t hesitate to seek help or learn from others’ experiences.

Transitioning to GraphQL isn’t just about changing tools—it’s about rethinking how you interact with data. Start small, experiment, and enjoy the journey!

REST vs. GraphQL: A Quick Comparison

When deciding between REST and GraphQL, understanding the key differences can help you make the right choice for your project. Here’s a quick breakdown:

Feature	REST API	GraphQL
Data Fetching	Fixed data structure for endpoints; can lead to over-fetching or under-fetching.	Flexible queries; fetch exactly what you need.
Endpoint Management	Multiple endpoints for different resources.	Single endpoint for all queries and mutations.
Flexibility	Limited flexibility; requires custom endpoints for specific data needs.	Highly flexible; client defines data requirements.
Type Safety	Relies on documentation; no built-in type enforcement.	Strongly-typed schema ensures predictable data.
Error Handling	Custom error formats; inconsistent across APIs.	Standardized error responses from schema validation.
Tooling	Varied and often endpoint-specific tools.	Rich ecosystem with tools like Apollo, GraphQL, and Relay.

While REST APIs are reliable and widely supported, GraphQL shines in scenarios requiring complex, interrelated data and flexibility.
Delve more into the differences in my previous article

Conclusion

Transitioning from REST to GraphQL has been a game-changer for me. The flexibility, efficiency, and improved developer experience have made my projects more robust and scalable. That said, I firmly believe REST APIs and GraphQL can coexist, complementing each other for different use cases.

If you’re considering making the switch, I encourage you to start small, experiment, and gradually integrate GraphQL into your stack. It’s a journey worth embarking on, and I’m excited to see how you make it your own.

Resources to Get Started

Here are some tools and guides to help you dive into GraphQL:

• GraphQL Documentation
• Apollo Server Guide
• GraphQL Playground

Bentil here 🚀
Have you transitioned from REST to GraphQL, or are you considering making the switch? What challenges or successes have you experienced along the way? Feel free to share your thoughts, questions, or experiences in the comments below. Let’s grow and learn together! 🚀