GraphQL API Development for Web Applications

Developing a complex web application often hits the problem: REST endpoints either return excessive data or require N requests for one screen. One of our projects—an analytics interface with a dozen widgets—required 15 REST calls to load the page. GraphQL solved that: the client requests exactly the needed fields and gets them in one response. Over-fetching and under-fetching disappear. A properly designed GraphQL API reduces traffic by 40–60% and accelerates frontend development. Developers get strict typing via schema introspection—fewer errors, faster iterations. We guarantee schema quality, resolver optimization, and full documentation.

Contact us to order GraphQL API development and get an engineer consultation—we'll help design a performant solution for your tasks.

Why Choose GraphQL over REST?

GraphQL is advantageous when multiple clients (web, mobile), complex nesting, and frequent requirement changes exist. It can reduce transferred data volume by 2–3 times compared to REST. Infrastructure savings are significant, and reducing the number of requests lowers database load by 40%.

Core GraphQL Concepts

Schema-first

API is defined through types:

type Article {
  id: ID!
  title: String!
  body: String!
  author: User!
  tags: [Tag!]!
  createdAt: DateTime!
}

type Query {
  article(id: ID!): Article
  articles(filter: ArticleFilter, page: Int, limit: Int): ArticleConnection!
}

type Mutation {
  createArticle(input: CreateArticleInput!): Article!
  updateArticle(id: ID!, input: UpdateArticleInput!): Article!
}

type Subscription {
  articleUpdated(id: ID!): Article!
}

Queries and Fragments

# Client requests only needed fields
query ArticlePage($id: ID!) {
  article(id: $id) {
    title
    body
    author {
      name
      avatar
    }
    tags { name, slug }
  }
}

# Reusable fragments
fragment ArticleCard on Article {
  id, title, slug
  author { name }
  createdAt
}

query ArticleList {
  articles(limit: 10) {
    nodes { ...ArticleCard }
    pageInfo { hasNextPage, endCursor }
  }
}

How to Solve the N+1 Query Problem with DataLoader

The main technical challenge of GraphQL is N+1 queries. For a list of 20 articles with the author field, it would be 1 + 20 = 21 SQL queries. This reduces performance and increases database load.

Solution — DataLoader (Facebook, ports for all languages):

const userLoader = new DataLoader(async (userIds: readonly string[]) => {
  const users = await db.user.findMany({
    where: { id: { in: [...userIds] } }
  });
  return userIds.map(id => users.find(u => u.id === id));
});

// In resolver
const articleResolver = {
  author: (article, _, { loaders }) => loaders.user.load(article.authorId),
};
// Now: 1 query for articles + 1 batch query for all authors

DataLoader batches requests and caches results within a single HTTP request. This is a key pattern for GraphQL API performance. For 20 articles, only 2 queries execute instead of 21—a 90% reduction, directly cutting database costs by up to 40%.

Implementing GraphQL API on Node.js

import { ApolloServer } from '@apollo/server';
import { makeExecutableSchema } from '@graphql-tools/schema';

const typeDefs = gql`...`;

const resolvers = {
  Query: {
    article: async (_, { id }, { db }) =>
      db.article.findUnique({ where: { id } }),

    articles: async (_, { filter, page = 1, limit = 20 }, { db }) =>
      db.article.findMany({
        where: filter ? { status: filter.status } : undefined,
        skip: (page - 1) * limit,
        take: limit,
      }),
  },

  Mutation: {
    createArticle: async (_, { input }, { db, user }) => {
      if (!user) throw new GraphQLError('Unauthorized', {
        extensions: { code: 'UNAUTHENTICATED' }
      });
      return db.article.create({ data: { ...input, authorId: user.id } });
    },
  },
};

const server = new ApolloServer({ schema: makeExecutableSchema({ typeDefs, resolvers }) });

Subscriptions

subscription CommentAdded($articleId: ID!) {
  commentAdded(articleId: $articleId) {
    id, body, author { name }
  }
}

Implementation via WebSocket (graphql-ws) + Redis Pub/Sub for scaling across instances.

Persisted Queries

For production applications: the client sends a hash of the query instead of the full text. Reduces traffic and enables CDN caching.

How to Design a GraphQL Schema: Step-by-Step Guide

1. Identify domain objects (entities) and their relationships.
2. Create types for each entity with explicit fields.
3. Develop input types for mutations.
4. Implement Query for reading data with pagination and filtering.
5. Implement Mutation for create, update, and delete.
6. Add Subscription for real-time events if needed.
7. Configure authorization at the field level using graphql-shield.
8. Test resolvers with unit and integration tests.

GraphQL API Security

Authorization is built at the resolver level using graphql-shield. Rules check user context and data. For authentication, we use JWT tokens. Rate limiting is done at the reverse proxy (Nginx) or middleware level.

What's Included in Turnkey GraphQL API Development

Our Expertise and Timelines

Team of certified developers with 7+ years of experience. We have delivered over 50 GraphQL projects, including high-load systems with millions of requests per day. We guarantee 99.9% SLA.

Timelines: GraphQL API (10–20 types, queries + mutations, DataLoader, authorization): 2–4 weeks. With subscriptions, persisted queries, federation (micro-services): 1–2 months.

We'll evaluate your project for free. Contact us to order turnkey GraphQL API development and get a consultation. Get a consultation on schema design and performance optimization—we'll help.

API Development with REST, GraphQL, WebSocket, and tRPC

A client comes to us with a Postman collection of 200 endpoints and says: 'Everything works, but the frontend is slow.' We open the Network tab — 47 sequential requests to load one dashboard page. Each one waits for the previous. This is not a server speed issue — it's an API architecture problem. With 10 years on the market, we've redesigned dozens of such integrations, and we guarantee: the right protocol and contract solve the problem at its root.

When REST stops being enough

REST works well for simple CRUD operations. But as soon as a mobile app appears alongside the web interface, over-fetching begins: the mobile app requests /api/users/123 and gets a 4KB object, but only needs name and avatar. Multiply that by a list of 50 users — 200KB traffic instead of 8KB.

GraphQL solves this with selection sets. The client describes exactly the fields it needs, and the server returns only those. On a project with React Native + Next.js, we migrated from REST to Apollo Server: payload size on the main screen dropped from 340KB to 28KB — a 92% traffic savings. Our certified engineers confirm: the typical pain when adopting GraphQL is N+1 query. A resolver for the author field on a post calls SELECT * FROM users WHERE id = ? for each post in the list. On a page with 20 posts — 21 database queries. Solved with DataLoader — it batches queries and turns them into one SELECT * FROM users WHERE id IN (...).

What is tRPC and how is it better than REST/GraphQL?

If the entire stack is TypeScript (Next.js + Node/Bun), tRPC removes a whole layer of problems. You define a procedure on the server — the client gets full type-safety automatically, without code generation and without Swagger. Renamed a field in the Zod schema — TypeScript highlights all places on the frontend where it's used. tRPC reduces code by 2 times compared to REST + Swagger + openapi-typescript: no need to maintain a separate specification and generate types — everything is inferred from runtime validators. However, tRPC is not suitable if the API is consumed by third-party clients or mobile apps in other languages — in such cases we use GraphQL or REST with OpenAPI specification.

WebSocket and real-time: when SSE, when WS?

HTTP polling every 5 seconds is an illusion of real-time with up to 5 seconds delay and useless server load. For chats, live notifications, collaborative editing — WebSocket or Server-Sent Events. SSE is a one-way stream from server to client, works over ordinary HTTP, automatically reconnects. Suitable for notifications, data streaming, progress bars. WebSocket is bidirectional, needed for chats and collaborative features. Experience shows: 80% of 'real-time' tasks are solved with SSE, not WebSocket — fewer infrastructure complexities.

A typical mistake: opening a WebSocket connection for each page component. On one project, the dashboard opened 12 parallel WS connections. The correct approach is one connection manager at the application level, subscriptions through it. In our work results, we always transfer the connection scheme and a ready solution.

Swagger / OpenAPI as a contract

Documentation written after the fact becomes outdated the day after release. We write the OpenAPI 3.1 specification before development starts; it becomes the contract between frontend and backend. The frontend generates types via openapi-typescript, the backend validates incoming data using generated schemas. Contract deviation from implementation is caught on CI, not during review. For Laravel — l5-swagger or dedoc/scramble. For Node.js — @fastify/swagger or Zod + zod-to-openapi.

How to properly authenticate an API?

JWT with long-lived access tokens without rotation is a source of problems when compromised. The correct scheme: access token for 15 minutes, refresh token for 30 days with rotation on each use. Refresh token stored in an httpOnly cookie, access token in memory (not in localStorage). For inter-service communication — API Keys with scope limitations or mTLS. OAuth 2.0 with PKCE for public clients (SPA, mobile).

How to handle versioning and backward compatibility?

Breaking changes in an API without versioning break clients. Three approaches we use in projects:

We guarantee backward compatibility through automated checks (oasdiff) on CI.

How we develop APIs: step-by-step plan

1. Analysis — audit of current integrations, data schema compilation, protocol selection (REST/GraphQL/tRPC/WebSocket).
2. Contract design — OpenAPI or SDL (GraphQL) before the first line of code.
3. Development — implementation per contract, unit tests for each endpoint.
4. Load testing — k6: 500 virtual users, 10 minutes, p95 latency ≤ 200ms.
5. Deployment — CI/CD with backward compatibility check, automatic documentation publication.
6. Team training — handover of Postman collection or Playground, connection instructions.

What is included (deliverables)

• OpenAPI 3.1 specification (or SDL for GraphQL).
• Generated client types for TypeScript / Dart / Kotlin.
• Set of automated tests covering all endpoints (unit + integration).
• Load tests (k6) and report (p50/p95/p99 latency, RPS).
• Documentation in Swagger UI / Redoc / GraphiQL.
• Team training (2–4 hour workshop).
• Support for 30 days after delivery (per contract).

Our experience

• 10+ years in the API development market.
• 200+ completed projects (REST, GraphQL, WebSocket, tRPC).
• 50+ certified engineers (AWS, Kubernetes, API Design).
• Traffic savings averaging 85% when migrating from REST to GraphQL for mobile apps.
• 100% backward compatibility — not a single broken client in the last 3 years.

Timeline

API development for a typical SaaS project with 30–50 endpoints: from 3 to 8 weeks depending on business logic complexity and number of external integrations. Migration of an existing REST API to GraphQL: from 2 to 6 weeks. Adding a WebSocket layer to an existing backend: from 1 to 3 weeks. Cost is calculated individually after an audit. Get a consultation — contact us to discuss your project.