APIs serve as the backbone of modern web development. They allow the front end of your application to communicate seamlessly with the backend, retrieve data, and trigger actions. But not all APIs are created equal. Two dominant approaches—REST and GraphQL—shape how data is exchanged, how flexible your system is, and how easy it is to evolve. Choosing the right architecture matters because it affects performance, developer productivity, and long-term maintainability. In this article, I’ll compare GraphQL and REST in-depth and help you decide which one suits your custom web development project best.
What is an API?
Before comparing GraphQL and REST, let’s clarify what an API actually is and why architecture matters.
An API (Application Programming Interface) defines a contract by letting your web client talk to your server and fetch or modify data. That might sound straightforward, but the architecture underlying that communication determines everything: how many requests you send, how much data you fetch, how easy it is to change your API later, and how costly it becomes to maintain.
The architecture affects:
- Performance: The way you structure your API can reduce or increase network load.
- Scalability: As your app grows, an API that scales efficiently will save you headaches.
- Developer productivity: A flexible API empowers front-end teams to build faster.
- Maintainability: A thoughtful architecture makes your API easier to version and extend.
Because of these stakes, the choice between GraphQL and REST is not trivial — it can make or break your long-term development experience.
What is REST?
REST (Representational State Transfer) is a long-established style of designing web APIs. It treats data as resources identified by URLs (endpoints), and relies on the standard HTTP methods — GET, POST, PUT, DELETE — to operate on them.
In a RESTful API, each resource (e.g., /users, /orders/123) maps to a fixed endpoint. The structure of the data returned is predetermined by the endpoint’s implementation. Clients don’t control the shape of what they fetch; they just hit endpoints and receive whatever the server sends back.
REST’s simplicity comes from its familiarity. Most developers already know how to work with HTTP, JSON, and RESTful URLs, which makes adoption relatively simple.
How REST APIs Work
When a client sends a request to a REST API, the server identifies which endpoint it is, executes the required logic (CRUD operations, business rules), and returns a response, usually in JSON. The client then processes the response. Because each endpoint has a fixed URL, it’s easy to cache responses using built-in HTTP cache mechanisms (like Cache-Control headers).
However, as your API grows, you often face “endpoint proliferation” — you may need many endpoints to support different kinds of data relationships (for example, /users/123/orders, /users/123/friends, /products/456/reviews). That can make the API complex and harder to maintain.
Strengths of REST
- Maturity and ecosystem: REST has existed for decades. The developer ecosystem is rich with tools like Swagger/OpenAPI for documentation, and nearly every language supports REST well.
- Caching: REST leans heavily on HTTP’s built-in caching mechanisms. GET requests can be cached based on URL and headers, and intermediaries (CDNs, browser caches) work naturally.
- Predictability: Because each endpoint returns a predetermined resource structure, developers know exactly what to expect. This makes REST good for public APIs or stable data models.
- Simplicity: For simple CRUD (Create, Read, Update, Delete) operations, REST’s paradigm aligns closely with how many traditional applications are built.
Limitations of REST
- Over-fetching: REST often returns more data than a client needs. For example, fetching a user endpoint may include every field, even if the client only needs the name.
- Under-fetching: The flip side is when a client needs nested or related data (e.g., user → posts → comments). REST may force multiple round-trip requests to gather everything.
- Versioning pain: As your API evolves, you’ll often need to create versioned endpoints (/v1/users, /v2/users) to avoid breaking existing clients.
- Scaling complexity: While REST can scale, high churn in endpoints or complex data relationships may introduce overhead in managing and optimising many endpoints.
What is GraphQL?
GraphQL originated at Facebook (now Meta) and offers a fundamentally different way to build APIs: instead of multiple endpoints, you typically deal with one /graphql endpoint. Clients send queries or mutations (for modifying data) and define exactly what they need. GraphQL also supports subscriptions for real-time updates.
GraphQL uses a strongly typed schema. The schema defines the types (objects, fields) and operations (queries, mutations, subscriptions). Clients must conform to that schema, and servers resolve each field via resolvers — functions that know how to fetch or compute that field.
How GraphQL Works
When a client sends a GraphQL query, it describes precisely the shape of the data it wants — which nested fields, how deeply, what filters. The server examines the schema and invokes the right resolvers to fetch the data, then responds with a JSON object that matches the shape of the query.
This design gives clients full control over what they fetch. They don’t get extra fields they don’t need, and they don’t need to hit multiple endpoints to get related data. The schema defines types and relationships, acting as a contract between client and server.
Strengths of GraphQL
- Precise data fetching: Clients request only what they need, cutting down on over-fetching.
- Nested queries: You can traverse relationships (like user → posts → comments) in a single request.
- Strong type system & self-documentation: GraphQL schemas are self-documenting, and tools can introspect them to generate docs automatically.
- Evolution without versioning: You can deprecate fields over time, but keep the same schema accessible so older clients don’t break.
- Real-time data: Subscriptions give you built-in real-time capabilities out of the box.
- Flexibility for multiple clients: Because clients (web, mobile, admin UI) might need different data, GraphQL lets each one request what’s relevant for them.
Limitations of GraphQL
- Caching is more complex: Because queries are flexible and hit a single endpoint, HTTP caching doesn’t apply cleanly. You often rely on client-side caching tools (like Apollo’s InMemoryCache) or custom strategies.
- Server complexity: You must build resolvers for fields, set up your schema, and possibly write complex logic. That introduces overhead.
- Resource consumption: Highly nested queries can cost CPU. In some empirical studies, GraphQL consumed more CPU than REST.
- Security risk: Because clients control queries, you need to enforce depth limits, complexity analyses, and possibly authentication strategies.
- Learning curve: Teams unfamiliar with GraphQL will need time to adopt schema design, query language, and resolver patterns.
GraphQL vs. REST Comparison
Data Fetching
With REST, you hit a resource endpoint and get everything that endpoint defines. If you need nested or related data, you often chain requests. GraphQL flips that: clients build a query to shape exactly what they want, including relationships.
Performance
GraphQL can reduce over-fetching and round-trips, which helps when bandwidth or latency matters (e.g., mobile applications). But on the server side, each GraphQL query must be parsed, validated, and resolved, which can consume more CPU than a simple REST GET.
Scalability
REST scales well in traditional microservice architectures, especially when endpoints map cleanly to services. GraphQL, meanwhile, can act as a gateway that aggregates data from multiple services, providing a unified API surface.
Developer Experience
GraphQL often appeals more to front-end developers because they fully control what they ask for. They iterate fast without constantly asking backend teams to add or change endpoints. On the other hand, REST’s simplicity and ubiquity make it familiar and fast to onboard.
Real-Time Capabilities
If you need real-time updates (for chat apps, dashboards, live feeds), GraphQL’s subscription model is powerful. REST, by contrast, lacks built-in real-time support and relies on WebSockets, SSE (Server-Sent Events), or polling.
Security
GraphQL’s flexibility introduces potential risk: deeply nested or malicious queries can overload your server, or expose data that should remain private. To guard against this, you must impose query complexity limits, validate inputs, and enforce authorisation per field. REST, being more rigid, is often easier to protect using standard HTTP security patterns and mature tooling.
Versioning & Evolvability
GraphQL allows for schema evolution. You can mark fields as deprecated without breaking existing consumers. With REST, you frequently resort to versioned endpoints, which may fragment your API and complicate maintenance.
Choosing the Right API for Your Custom Web Development Project
Deciding between GraphQL and REST depends heavily on your project’s specific needs. Here are some guidelines:
REST makes more sense to use when:
- You build a simple, CRUD-based application (e.g., an admin dashboard, content management system).
- You rely heavily on caching to improve performance (REST’s HTTP caching fits naturally).
- Your data model is fairly flat, with few nested relations.
- Your team has limited experience with GraphQL, or you want to minimise learning overhead.
- You are designing a public-facing API for external developers: REST’s predictability and standard tooling (Swagger/OpenAPI) make onboarding easier.
- You need to adhere to compliance or auditing constraints. With REST, versioned endpoints and HTTP status codes simplify change control.
When GraphQL is the right fit
- Your app fetches complex, nested data, and different clients (mobile, web, admin) need different shapes of that data.
- Bandwidth matters (for mobile or low-bandwidth environments). With GraphQL, clients fetch only what they need, reducing wasted data.
- You want real-time or subscription features (chat, live dashboards).
- Your team values developer agility: front-end developers can drive feature changes without always asking backend teams to add endpoints.
- You aim for long-term API evolution: GraphQL enables backwards-compatible changes, so you can deprecate fields without breaking existing clients.
- You’re aggregating data from multiple sources (microservices, databases, third-party APIs) and want a unified API layer.
When a Hybrid approach works
Sometimes you don’t have to choose one exclusively.
- Use GraphQL as a gateway while backing it with microservices that expose REST endpoints. This gives you flexibility and performance, without throwing away existing service architecture.
- Or, maintain a GraphQL API internally for your own front-ends, but expose a REST API to external consumers who prefer simplicity and standard rules. Some teams generate REST routes from a GraphQL schema using tools like graphql2rest.
Key Factors to Evaluate Before Deciding
Before you pick an API architecture, run through these considerations:
- Project complexity: How complex are your data relationships? Do you foresee many nested queries?
- Client diversity: Do multiple front-ends (web, mobile, admin) need different views of the data?
- Performance requirements: Do you need to optimise for bandwidth, latency, or CPU cost?
- Team expertise: How comfortable is your team with GraphQL schema design and resolver logic?
- Maintenance: How often will your API evolve? Do you need to support backward compatibility?
- Infrastructure: Do you have the right tools and monitoring in place to handle GraphQL’s dynamic queries?
- Security: Are you prepared to limit query complexity and enforce per-field authorisation?
Conclusion
GraphQL and REST both remain powerful, viable API architectures — but they shine in different contexts. REST offers simplicity, caching efficiency, and maturity. GraphQL provides flexible data fetching, developer agility, and real-time support.
You don’t need to bet your entire future on one. Many teams leverage a hybrid approach that gives them the best of both worlds. Choose based on your project’s specific requirements, your team’s strengths, and your long-term vision.
If your application involves complex data, multiple clients, or real-time features, GraphQL likely serves you best. If you want straightforward CRUD operations, reliable caching, and a simple path forward, REST remains a robust choice.