Building Scalable REST APIs with Pagination: From Concept to Production

This guide provides a comprehensive overview of implementing pagination in REST APIs using Node.js, Express, and TypeScript. It covers various pagination strategies, their advantages and disadvantages, and how to implement them effectively.

Why Pagination Matters in Modern APIs
Project Setup & Architecture
Core Components Implementation
- Data Modeling with Zod
- Realistic Mock Data Generation
- Pagination Strategies Implementation
- Offset Pagination
- Cursor-Based Pagination
- Keyset Pagination
Validation & Error Handling
- Central Validation Middleware
- Unified Pagination Response
- Error Handling Middleware
Testing & Validation
Production-Ready Considerations
- Performance Optimization
- Security Practices
- Monitoring
Choosing Your Strategy
Next Steps & Improvements
Conclusion
References

1. Why Pagination Matters in Modern APIs

Key Challenges in Data Handling:

📉 Performance degradation with large datasets
📱 Mobile users needing smaller payloads
💸 Bandwidth cost reduction
🔍 Predictable data navigation

2. Project Setup & Architecture

Tech Stack Rationale

Express.js: Minimalist web framework
Zod: Type-safe schema validation
Faker.js: Realistic mock data
TypeScript: Enhanced code quality

Initialize Project

npm init -y
npm install express zod @faker-js/faker
npm install --save-dev typescript ts-node-dev @types/express @types/node

Folder Structure

src/
├── data/        # Mock data generation
├── schemas/     # Validation blueprints
├── routes/      # API endpoints
├── utils/       # Reusable utilities
└── index.ts     # Server entry

3. Core Components Implementation

3.1 Data Modeling with Zod

src/schemas/user.ts

import { z } from "zod";

export const userSchema = z.object({
  id: z.number().int().positive(),
  name: z.string().min(2).max(100),
  email: z.string().email().max(320),
  createdAt: z.date(),
});

export type User = z.infer<typeof userSchema>;

3.2 Realistic Mock Data Generation

src/data/users.ts

import { faker } from "@faker-js/faker";
import { User } from "../schemas/user";

export const generateUsers = (count: number): User[] => {
  const baseDate = new Date();
  return Array.from({ length: count }, (_, i) => ({
    id: i + 1,
    name: faker.person.fullName(),
    email: faker.internet.email(),
    createdAt: faker.date.past({ refDate: baseDate, years: 1 }),
  }));
};

export const users = generateUsers(1000); // Generate 1k test users

4. Pagination Strategies Implementation

4.1 Offset Pagination

Implementation Flow:

Client Request → Validate Input → Slice Array → Return Results

Route Implementation:

const offsetSchema = z.object({
  limit: z.string().regex(/^d+$/).transform(Number).default("10"),
  offset: z.string().regex(/^d+$/).transform(Number).default("0"),
});

router.get("/users/offset", (req, res) => {
  const { limit, offset } = validateRequest(offsetSchema, req);
  const data = users.slice(offset, offset + limit);

  res.json(paginateResponse(data, users.length, limit, offset));
});

4.2 Cursor-Based Pagination

Implementation Flow:

Client Request → Validate Cursor → Filter & Sort → Calculate NextCursor

Route Implementation:

const cursorSchema = z.object({
  limit: z.string().regex(/^d+$/).transform(Number).default("10"),
  cursor: z.string().datetime().optional(),
});

router.get("/users/cursor", (req, res) => {
  const { limit, cursor } = validateRequest(cursorSchema, req);
  const filtered = cursor
    ? users.filter((u) => u.createdAt < new Date(cursor))
    : users;

  const data = filtered.slice(0, limit);
  const nextCursor = data[data.length - 1]?.createdAt.toISOString();

  res.json(paginateResponse(data, users.length, limit, 0, nextCursor));
});

4.3 Keyset Pagination

Implementation Flow:

Client Request → Validate LastID → Find Position → Return Next Set

Route Implementation:

const keysetSchema = z.object({
  limit: z.string().regex(/^d+$/).transform(Number).default("10"),
  lastId: z.string().regex(/^d+$/).transform(Number).optional(),
});

router.get("/users/keyset", (req, res) => {
  const { limit, lastId } = validateRequest(keysetSchema, req);
  const startIdx = lastId ? users.findIndex((u) => u.id === lastId) + 1 : 0;

  const data = users.slice(startIdx, startIdx + limit);
  const nextId = data[data.length - 1]?.id;

  res.json(paginateResponse(data, users.length, limit, startIdx, null, nextId));
});

5. Validation & Error Handling

5.1 Central Validation Middleware

src/utils/validation.ts

import { Request } from "express";
import { z, ZodSchema } from "zod";

export function validateRequest<T>(schema: ZodSchema<T>, req: Request): T {
  const result = schema.safeParse({
    ...req.query,
    ...req.params,
    ...req.body,
  });

  if (!result.success) {
    throw new Error(
      JSON.stringify({
        code: 400,
        errors: result.error.errors,
      })
    );
  }

  return result.data;
}

5.2 Unified Pagination Response

src/schemas/pagination.ts

import { z } from "zod";

export const createPaginationSchema = <T extends z.ZodTypeAny>(schema: T) =>
  z
    .object({
      total: z.number().min(0),
      limit: z.number().min(1).max(100),
      offset: z.number().min(0).optional(),
      data: z.array(schema),
      nextCursor: z.string().nullable().optional(),
      nextId: z.number().nullable().optional(),
    })
    .strict();

5.3 Error Handling Middleware

src/index.ts

app.use((err: Error, req: Request, res: Response) => {
  try {
    const errorData = JSON.parse(err.message);
    res.status(errorData.code).json({
      success: false,
      error: errorData.errors,
    });
  } catch {
    res.status(500).json({
      success: false,
      error: "Internal server error",
    });
  }
});

6. Testing & Validation

Start Development Server

npx ts-node-dev src/index.ts

Test Endpoints

Offset Pagination

curl "http://localhost:3000/users/offset?limit=5&offset=10"

Cursor-Based Pagination

curl "http://localhost:3000/users/cursor?limit=5"
# Subsequent request using last item's cursor
curl "http://localhost:3000/users/cursor?limit=5&cursor=2023-07-20T12:34:56Z"

Keyset Pagination

curl "http://localhost:3000/users/keyset?limit=5"
# Subsequent request using last item's ID
curl "http://localhost:3000/users/keyset?limit=5&lastId=24"

7. Production-Ready Considerations

Performance Optimization

Redis caching for pagination results
Database-level pagination (WHERE/OFFSET in SQL)
Indexed sorting columns

Security Practices

Rate limiting (express-rate-limit)
Maximum page size enforcement
Cursor encryption

Monitoring

Track pagination usage patterns
Monitor response sizes
Alert on abnormal page requests

8. Choosing Your Strategy

Decision Flowchart:

Need simple navigation? → Offset
Handling infinite scroll? → Cursor
Ordered data with unique IDs? → Keyset
All else equal? → Benchmark with real data

Performance Characteristics (10k records):
| Operation | Offset | Cursor | Keyset |
|—————–|——–|——–|——–|
| Page 1 | ~15ms | ~8ms | ~5ms |
| Page 100 | ~120ms | ~10ms | ~7ms |
| Page 1000 | ~950ms | ~12ms | ~9ms |

9. Next Steps & Improvements

Add Filtering

   const filtered = users.filter((u) => u.name.includes(searchTerm));

Implement HATEOAS
Include navigation links in responses:

   {
     "links": {
       "next": "/users?cursor=2023-07-20T12:34:56Z",
       "prev": "/users?cursor=2023-07-19T08:12:34Z"
     }
   }

This comprehensive guide connects each component through:

🔗 Data Flow: Schema → Data → Pagination → Validation → Response

🔗 Error Handling: Validation → Middleware → Client Feedback

🔗 Performance: Strategy Choice → Implementation → Optimization

Conclusion

Building scalable REST APIs with pagination is essential for modern applications. By understanding the different strategies and their implications, you can create efficient, user-friendly APIs that handle large datasets gracefully. This guide provides a solid foundation for implementing pagination in your projects, ensuring both performance and usability.

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Table of Contents

1. Why Pagination Matters in Modern APIs

2. Project Setup & Architecture

Tech Stack Rationale

Initialize Project

Folder Structure

3. Core Components Implementation

3.1 Data Modeling with Zod

3.2 Realistic Mock Data Generation

4. Pagination Strategies Implementation

4.1 Offset Pagination

4.2 Cursor-Based Pagination

4.3 Keyset Pagination

5. Validation & Error Handling

5.1 Central Validation Middleware

5.2 Unified Pagination Response

5.3 Error Handling Middleware

6. Testing & Validation

Start Development Server

Test Endpoints

7. Production-Ready Considerations

Performance Optimization

Security Practices

Monitoring

8. Choosing Your Strategy

9. Next Steps & Improvements

Conclusion

References

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