Confessions of a REST Developer: Why I’m Eyeing GraphQL

For as long as I can remember, my developer life has been built on a solid, reliable foundation of REST APIs. I knew the rules, I respected the conventions, and I accepted the quirks.

Need user details? GET /users/123. Need their posts? GET /users/123/posts. Need their comments? GET /users/123/posts/45/comments.

It felt normal. A bit like walking into a supermarket where every aisle only lets you buy one specific item per trip, forcing you to run back in six times just to make a sandwich. But hey—that was the price of clean architecture!

Then, GraphQL started showing up everywhere in my feed. At first, I ignored it. "Just another shiny JavaScript trend," I whispered to myself while quietly writing my fifth endpoint wrapper of the day. But curiosity got the better of me. I took the plunge, and honestly? It’s time for a confession.

The REST Quirks We Just Accepted

To understand why GraphQL feels so wild to a REST developer, we first have to admit the daily struggles we’ve learned to tolerate in REST land.

1. Over-fetching (The Buffet Problem)

Imagine ordering a simple side salad at a restaurant, but the waiter brings out a 12-course meal including a whole roasted turkey, three types of soup, and a dessert cart.

That’s over-fetching. You ask GET /users/123 just to display a simple profile badge with a name and avatar, but the API hands you:

• First name, last name, middle name, nickname.
• Home address, work address, billing address.
• Account creation timestamp, last login, password reset tokens.
• A nested object containing their entire life story.

Your mobile app’s data budget cries softly in the background.

2. Under-fetching & N+1 Requests (The Fetching Marathon)

Now picture the opposite. You want to render a single dashboard page showing a user, their top 3 recent posts, and the top comment on each post. In REST land, your frontend code turns into a marathon runner:

1. Fetch GET /user/123 (1 request)
2. Fetch GET /user/123/posts (1 request)
3. Loop through those posts to fetch comments for each (N requests)

Before you know it, your app has made 15 network requests just to render one screen. Your browser network tab looks like a waterfall of regret.

Enter GraphQL: The Menu-Style API

When I started playing around with GraphQL, the biggest mental shift was simple: Instead of hitting multiple endpoints to get fixed data structures, you send a single query to a single endpoint (/graphql) describing exactly what you want.

It’s like handing a custom grocery list to a waiter who goes to the kitchen and comes back with only the ingredients you asked for—nothing more, nothing less.

What a GraphQL Query Looks Like

Here is what blew my REST-oriented mind. If I only need a user's name and avatarUrl, I write a query like this:

query {
  user(id: "123") {
    name
    avatarUrl
  }
}

And the response looks identical in shape:

{
  "data": {
    "user": {
      "name": "Alex Developer",
      "avatarUrl": "https://example.com/avatar.png"
    }
  }
}

No bloated payload. No extra requests. Just pure, precise data efficiency. Need their top post titles too? You don't create a new endpoint called /GET /users-with-posts. You just update your query:

query {
  user(id: "123") {
    name
    avatarUrl
    posts(limit: 1) {
      title
    }
  }
}

First Impressions: The Good, The Cool, and The "Wait, What?"

As a REST developer dipping my toes in, here are my honest takeaways so far:

The Mind-Blowing Stuff 🤯

• Single Endpoint: Goodbye, endpoint sprawl. No more arguing over whether it should be /user/posts or /users/posts.
• Strong Typing out of the Box: GraphQL uses a schema written in Schema Definition Language (SDL). The API self-documents what fields exist and what types they return. Tools like GraphiQL let you test queries with autocomplete right in your browser.
• Frontend Empowerment: Frontend developers can adjust what data they fetch without waiting for backend devs to publish a new endpoint or update a DTO.

The "Wait, REST Didn't Have This Problem" Stuff 🤨

• Caching is... Different: With REST, HTTP caching (204 Not Modified, ETag, browser caching per URL) works out of the box. Because GraphQL sends everything via POST to a single /graphql endpoint, HTTP-level caching doesn't work the same way. You need client-side libraries like Apollo or Relay to handle caching.
• The N+1 Problem Shifted to the Backend: While GraphQL saves the client from making N+1 requests, the backend server now has to resolve all those nested fields efficiently (hello, DataLoader pattern!).
• Error Handling: In REST, a 404 Not Found or 401 Unauthorized status code tells a clear story. In GraphQL, you often get a 200 OK status with an errors array inside the response body. That takes some getting used to!

Am I Abandoning REST Forever?

Not at all. REST isn't going anywhere—it’s simple, predictable, and perfect for many use cases (like file uploads, simple CRUD apps, or public APIs where HTTP caching is crucial).

But exploring GraphQL has been an eye-opener. It solves real pain points that frontend and mobile teams face every day when dealing with complex, interconnected data.

If you're a REST developer who hasn't tried GraphQL yet, I highly recommend building a tiny prototype over a weekend. At worst, you'll appreciate how much REST does for you; at best, you'll fall in love with a whole new way to query data.

Are you team REST, team GraphQL, or currently living in a hybrid state of confusion like me? Let me know in the comments below!