SWR vs React Query: Choosing the Right Data Fetching Library

SWR and React Query are two prominent data-fetching libraries in the React ecosystem, each offering unique features and catering to different use cases. Understanding their differences can help developers select the most appropriate tool for their projects.

SWR (Stale-While-Revalidate)

Developed by Vercel, SWR is a lightweight React Hooks library focused on data fetching and caching. It operates on the "stale-while-revalidate" strategy, where it returns cached data (stale) first and then revalidates by fetching the latest data in the background.

Pros:

• Simplicity: SWR provides a straightforward API, making it easy to integrate into projects with minimal setup.
• Lightweight: With a smaller bundle size, SWR is suitable for applications where minimizing load times is crucial.
• Optimistic UI: It allows for optimistic UI updates, enhancing user experience by reflecting changes before the server responds.

Cons:

• Limited Features: SWR offers basic data fetching capabilities but lacks advanced features like pagination, polling, and mutations found in more comprehensive libraries.
• Manual Mutations: Handling data mutations requires manual implementation, which can be less intuitive compared to built-in solutions.

React Query (TanStack Query)

React Query is a robust library that provides a set of hooks and tools to fetch, cache, and update asynchronous data in React applications. It offers a comprehensive suite of features suitable for complex data-fetching scenarios.

Pros:

• Feature-Rich: React Query includes advanced features such as pagination, polling, mutations, and query invalidation, catering to complex data-fetching needs.
• Automatic Caching and Background Refetching: It automatically caches data and refetches in the background to keep the data up-to-date.
• Built-in Mutation Support: Provides built-in hooks for data mutations, simplifying optimistic UI implementations and state updates.

Cons:

• Larger Bundle Size: The extensive feature set contributes to a larger bundle size, which might impact performance in applications where size is a concern.
• Steeper Learning Curve: With its wide array of features and configurations, React Query may require a learning period to fully leverage its capabilities.

Comparative Overview

Feature	SWR	React Query
Bundle Size	Smaller (~15KB)	Larger (~50KB)
Caching	Basic caching with revalidation	Advanced caching with fine-grained control
Mutations	Manual implementation required	Built-in mutation hooks
Pagination Support	Basic support	Advanced pagination and infinite queries
Polling	Supported with manual setup	Built-in polling and refetching options
Learning Curve	Gentle learning curve	Steeper due to extensive feature set
Ideal Use Case	Simple applications with basic data needs	Complex applications requiring advanced data management

Code Examples

Using SWR:

import useSWR from 'swr';

const fetcher = (url: string) => fetch(url).then(res => res.json());

function UserProfile({ userId }: { userId: string }) {
  const { data, error } = useSWR(`/api/user/${userId}`, fetcher);

  if (error) return <div>Failed to load user data</div>;
  if (!data) return <div>Loading...</div>;

  return <div>Hello, {data.name}!</div>;
}

Using React Query:

import { useQuery, useMutation } from '@tanstack/react-query';

const fetchUser = async (userId: string) => {
  const response = await fetch(`/api/user/${userId}`);
  if (!response.ok) {
    throw new Error('Network response was not ok');
  }
  return response.json();
};

function UserProfile({ userId }: { userId: string }) {
  const { data, error, isLoading } = useQuery(['user', userId], () => fetchUser(userId));

  if (isLoading) return <div>Loading...</div>;
  if (error instanceof Error) return <div>An error occurred: {error.message}</div>;

  return <div>Hello, {data.name}!</div>;
}

Use Cases

• SWR: Ideal for applications requiring simple data fetching with minimal setup, where the focus is on fetching data from a single endpoint and displaying it without extensive data manipulation.
• React Query: Suited for complex applications with multiple data sources, requiring advanced features like pagination, real-time data synchronization, and comprehensive caching strategies.

Limitations

SWR:

• Lacks built-in support for mutations and complex data operations, necessitating custom implementations.
• Provides basic pagination support, which might not suffice for applications with intricate data structures.

React Query:

• The extensive feature set can lead to a larger bundle size, potentially affecting performance in applications where size is critical.
• The richness of features introduces a steeper learning curve, requiring time to master its full potential.

Conclusion

Both SWR and React Query are powerful tools for data fetching in React applications. SWR excels in simplicity and lightweight usage, making it suitable for straightforward data-fetching tasks. In contrast, React Query offers a comprehensive suite of features designed for complex data management scenarios. The choice between the two should be guided by the specific requirements and complexity of your application.