GraphQL and REST are two popular approaches to building APIs. If you’re a junior developer or a student preparing for tech interviews, you’ve likely heard these terms. In simple words, REST is the traditional way of designing web APIs, while GraphQL is a newer query language for APIs that promises more flexibility. Understanding how GraphQL compares to REST will not only improve your API architecture skills but also help you in system design interviews and mock interview practice.

What is REST API Design?

REST (Representational State Transfer) is an architectural style for creating web services. In a RESTful API, the client and server communicate over HTTP using standard methods:

• Multiple endpoints: Different URLs (endpoints) represent different resources (e.g., /users, /orders).
• HTTP verbs: Clients use methods like GET (to read data), POST (to create), PUT/PATCH (to update), and DELETE (to remove) on those endpoints.
• Stateless calls: Each request stands alone with all needed info, and the server doesn’t remember state between calls. This makes REST APIs scalable and easy to maintain.
• Caching: REST responses can be cached (especially GET requests) to improve performance. Browsers and servers can store responses to reuse later.

In practice, a REST API is basically a web service that can be called with standard HTTP tools. It’s widely adopted because it’s simple and relies on HTTP – the backbone of the web.

What is GraphQL?

GraphQL is a query language for APIs developed by Facebook and released publicly in 2015. Unlike REST, GraphQL doesn’t use multiple endpoints for different data. Instead, it uses one endpoint (commonly /graphql) and a flexible query system:

• Single endpoint, many queries: You send a query describing exactly what data you want, and the server responds with exactly that. For example, a GraphQL query can ask for a user’s name and their recent posts in one request, instead of calling /users and then /posts separately as you might in REST.
• No overfetching: GraphQL gives clients the power to ask for exactly what they need and nothing more. This avoids getting a bunch of unnecessary data (overfetching) or needing multiple calls for missing data (underfetching).
• Strongly-typed schema: GraphQL uses a schema with types (like User, Post with fields) that the server defines. Clients can only query what’s in the schema, which means errors are caught early and APIs are self-documented.
• Operations instead of verbs: GraphQL has queries (to read data), mutations (to modify data), and subscriptions (for real-time updates). Under the hood, these are usually sent as HTTP POST requests to the GraphQL endpoint.

GraphQL’s flexibility lets you get multiple pieces of data in a single round trip. Apps using GraphQL can be quick even on slow networks because one request can fetch all needed info. However, GraphQL also introduces new complexity in setting up a server and writing resolvers (functions that map queries to data).

GraphQL vs REST: Key Differences in API Design

How do GraphQL and REST differ in practice?

Below is a side-by-side comparison of key aspects:

Aspect	REST API	GraphQL
Endpoints	Multiple endpoints (different URLs) for different resources or actions.	Single endpoint (usually /graphql) for all data queries and mutations.
Data returned	Fixed response structure (server decides). Can include extra data you might not need (overfetching), or you might call multiple endpoints to gather all data (underfetching).	Flexible response (client specifies fields in query). Returns only the requested data, avoiding overfetching and underfetching.
Caching	Built-in HTTP caching (especially for GET requests) via browsers or CDNs. Each resource URL can be cached.	Not cache-friendly by default (uses a single URL and often POST requests). Requires custom caching strategies or tools for effective caching.
Schema & Type Safety	No strict type system by default (optional documentation or OpenAPI/Swagger for specs). Clients must follow API docs, but there’s no enforcement at the protocol level.	Strongly-typed schema on the server defines available data types and relationships. Queries are validated against the schema for correctness.
Versioning	Often versioned with new endpoints (e.g., /api/v1/ vs /api/v2/) when changes are made, to avoid breaking existing clients.	Usually versionless. The schema evolves by adding or deprecating fields without breaking existing queries, so one GraphQL endpoint can stay compatible over time.
Learning Curve	Simple and familiar. Uses standard HTTP methods and JSON, so it’s easy to learn and widely supported.	Steeper learning curve. Developers must learn GraphQL syntax and set up a GraphQL server. More upfront work, but it offers more flexibility once learned.

As you can see, GraphQL focuses on flexibility and efficiency, while REST emphasizes simplicity and convention. GraphQL allows clients to avoid over- or under-fetching by requesting only what they need, which can reduce network calls. On the other hand, REST’s straightforward nature and built-in caching make it a reliable choice for many basic use cases.

Interview Tip: If you’re asked about GraphQL vs REST in a system design interview, mention these trade-offs. For example, GraphQL provides precise data fetching and avoids multiple calls, whereas REST is simpler to cache and can be easier to implement. Showing you understand the why behind each approach is a great technical interview tip.

When to Use GraphQL vs REST

Both GraphQL and REST are useful, but in different scenarios. Here are some guidelines on when to choose one over the other:

Choose GraphQL if:

• You need to fetch complex, related data in a single request (e.g. loading a dashboard with multiple data types).
• Different clients (web, mobile) have different data needs. GraphQL’s flexibility can reduce the number of API calls and data transfer, making your app more efficient.
• You want a strongly-typed API that clearly defines data models, which can help catch errors early and improve collaboration between frontend and backend teams.
• Avoiding API versioning is a priority. GraphQL lets you evolve your API without breaking existing queries, by adding new fields over time.

Choose REST if:

• You prefer simplicity and quick integration. For small apps or straightforward CRUD (Create, Read, Update, Delete) operations, a RESTful API is often faster to set up and understand.
• Caching and CDN support are crucial. If your app benefits from HTTP caching (like serving largely static data), REST is a natural fit.
• You have a public API that many clients use. REST’s predictability and wide adoption make it easier for others to use without specialized tooling.
• Your team is new to API development or needs a gentle learning curve. REST’s concepts (URLs, HTTP verbs, JSON) are more familiar to most developers.

Keep in mind, these are not hard rules. Many modern systems even use a mix of both: for example, using REST for simple services and GraphQL for more complex data fetching needs. It’s all about using the right tool for the job in your system architecture.

FAQs

Q1. What is GraphQL in simple terms?

GraphQL is a query language for APIs that lets the client ask for exactly the data it needs. Instead of hitting multiple REST endpoints, a client sends a GraphQL query to one endpoint and gets everything back in one response. This makes data fetching more efficient and flexible.

Q2. Is GraphQL better than REST?

GraphQL isn’t strictly “better” than REST; they serve different needs. GraphQL excels at giving clients flexibility and reducing multiple API calls by fetching many resources at once. REST is better for simple APIs, easy caching, and quick development. The best choice depends on your project’s requirements and constraints.

Q3. When should I use REST vs. GraphQL?

Use REST when you want simplicity, robust caching, and well-understood conventions (for example, a small service or public API). Use GraphQL when your clients need more complex data interactions, such as pulling related data in one go, or when you want to avoid maintaining multiple API versions. Often, small projects start with REST, while GraphQL shines in complex, data-rich applications.

Q4. Does GraphQL replace REST in modern APIs?

GraphQL doesn’t outright replace REST; it complements it. Many companies still use REST heavily, and some adopt GraphQL for specific use cases (like feeding a complex UI). GraphQL solves certain problems of REST (like overfetching/underfetching) but introduces new considerations (like caching and complexity). In modern API design, it’s common to choose the approach that best fits each service.

Conclusion

GraphQL and REST are both powerful tools in API design and system architecture. In summary, GraphQL offers a flexible query-based approach where clients define what data they need, often leading to fewer network calls and no overfetching. REST offers a resource-based approach with clear and simple endpoints, leveraging HTTP methods and caching for reliability.

For beginners and those preparing for system design interviews, remember these key points:

• GraphQL = Flexibility & Single Endpoint: Great for complex data needs and fast iterations, but requires learning its schema and query syntax.
• REST = Simplicity & Standard HTTP: Great for quick development and caching, but can require multiple calls to compose data.

Ultimately, knowing both will make you a stronger developer. Many teams use REST and GraphQL together, picking the right tool for each job. By understanding their differences, you can confidently discuss API design choices in a technical interview or a mock interview practice session.

Interested in learning more about system design and API architecture? Don’t forget to check out our internal resources and courses. For an in-depth look at REST vs GraphQL (and even gRPC), read our blog post REST vs GraphQL vs gRPC – In-depth Comparison. To further level up your system design skills, explore our Grokking the System Design Interview course. DesignGurus.io is a leading platform for system design and coding interview preparation, and we’re here to help you ace your next interview!