GraphQL API Basics & Best Practices (Explained Simply)

Learn how to design clean, flexible, and powerful GraphQL APIs that solve over-fetching, under-fetching, and give clients full control over data.

Traditional REST APIs often return too much or too little data, requiring multiple requests for a single view.

GraphQL solves this by giving clients exactly what they need — no more, no less — in a single request.

But designing a GraphQL API isn’t the same as designing REST APIs.

In this article, we’ll walk through:

• Why GraphQL exists

• How to design a proper schema

• Queries and mutations

• Error handling and versioning

• Best practices for real-world GraphQL APIs

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Why GraphQL Exists

GraphQL was created at Facebook to solve a growing frontend problem: mobile apps and web views needed precise, predictable data, but REST APIs often returned too much, too little, or the wrong shape entirely.

GraphQL solves this by letting the client specify the exact shape of the response.

A few key features:

• Single endpoint for all data interactions

• Typed schema defines what data is available

• Transport-agnostic, though often used over HTTP POST

Instead of stitching together data from multiple REST endpoints, clients ask for exactly what they need in a single GraphQL query.

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Schema Design and Type System

Your schema is the contract between the client and server.

It defines:

• Types (e.g. User, Post, Comment)

type User {
  id: ID!
  name: String!
  posts: [Post!]!
}

• Queries to fetch data

type Query {
  user(id: ID!): User
}

• Mutations to write data

type Mutation {
  createUser(name: String!): User
}

Good schema design mirrors your domain model. It should feel natural to clients consuming the API.

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Queries, Mutations, and Subscriptions

Queries: Fetch data

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

Mutations: Modify data

mutation {
  createPost(title: "New Post", body: "Hello") {
    id
    title
  }
}

Subscriptions: Get real-time updates (usually via WebSockets)

subscription {
  postAdded {
    id
    title
  }
}

All three operations use the same endpoint — the only difference is the payload and operation type.

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Error Handling and Versioning

GraphQL handles errors differently than REST.

Even if something fails, GraphQL returns a 200 OK status and includes an errors field in the response:

{
  "data": { "user": null },
  "errors": [
    {
      "message": "User not found",
      "path": ["user"]
    }
  ]
}

Partial data + errors is perfectly valid. This gives clients more control over fallback behavior.

Versioning

GraphQL avoids versioning through schema evolution:

• Use @deprecated to phase out old fields

• Add new fields as needed

• Keep old ones alive until no longer used

This lets your API evolve without breaking existing clients.

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GraphQL API Best Practices

Designing a powerful GraphQL API means thinking ahead. Here are some best practices:

• Keep your schema modular and domain-driven

• Prevent abuse with query depth limits or cost analysis

• Avoid overly deep nesting — it can crush performance

• Use input types for mutations

• Use clear, consistent names for fields and types

These principles help you build APIs that scale with your product.

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Final Thoughts

You’ve learned:

• Why GraphQL exists and how it improves on REST

• How to design types, queries, and mutations

• How to handle errors and evolve your schema

• Best practices for real-world API design

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