Most web developers recognize the importance of APIs in enabling clients and servers to communicate with each other. The design of your API will affect how well it works, how well it scales, and how well users like it, whether you’re making a mobile app, a web app, or a big SaaS product.
Over the years, two major approaches have emerged: REST (Representational State Transfer) and GraphQL.
But here’s the catch—while REST has been the long-standing industry standard, GraphQL has rapidly gained traction among developers for its flexibility and efficiency.
Choosing between the two isn’t as simple as picking what’s new; it’s about understanding how each fits your project’s needs.
In this guide, we will consider the performance, scalability, and developer experience for both GraphQL and REST. We aim to guide you in the right direction for API architecture in your upcoming modern web application.
APIs act as the communication layer between the front end and back end.
Imagine them as waiters in a restaurant, they take requests from customers (your app), bring them to the kitchen (your server), and return the results (your data). The more efficient this process is, the smoother your app feels.
With the rise of progressive web apps (PWAs), single-page applications, microservices, and mobile-first design, data fetching has become more complex. Clients no longer just need a single page of data — they often require multiple resources from various endpoints in real time.
This has led to developers seeking more efficient, flexible solutions. REST has served well for decades, but new challenges have made room for alternatives like GraphQL.
APIs enable front-end and back-end disaggregation for modular development. This independence helps parallel scaling and system development.
Whether it’s pulling product details in an e-commerce site, loading posts in a social media app, or syncing messages in a chat service, APIs are the unsung heroes making it happen.
Today’s apps rely on real-time updates, dynamic interfaces, and cross-platform compatibility. Effective UI/UX design ensures that these technical capabilities translate into seamless user experiences.
Complex queries can be a challenge for REST APIs to handle efficiently. Unlike REST APIs, GraphQL is a contemporary technology that enables systems to respond to clients with customized queries, providing only the necessary information and saving query time.
This difference in data fetching philosophy is one of the main reasons developers are moving toward GraphQL for modern, data-intensive applications.
REST, or Representational State Transfer, was introduced by Roy Fielding in his 2000 doctoral dissertation. It quickly became the gold standard for designing websites due to its simplicity and scalability.
REST relies on standard HTTP methods—GET, POST, PUT, DELETE to manage resources, making it easy to understand and implement.
REST APIs rely on statelessness to handle requests because it allows a system to be more reliable and obtain better scalability. This approach to obtaining statelessness is a primary reason why REST APIs work efficiently as web-scale systems.
REST is based on six architectural constraints that define how web services should be designed:
REST has been a simple and scalable option for some time, but the evolution of interactive, data-heavy web applications has revealed REST’s limitations.
Advantages:
Limitations:
REST is robust and reliable, but it’s not always efficient for modern, data-driven front ends like React or Vue apps that demand precise data control.
GraphQL was developed by Facebook in 2012 and open-sourced in 2015. It was created to solve REST’s inefficiencies in fetching data for complex UIs. Instead of multiple endpoints, GraphQL provides a single endpoint through which clients can query exactly what they need.
GraphQL allows developers to request multiple resources in a single query, reducing network overhead. For instance, instead of calling /users, /posts, and /comments separately in REST, a single GraphQL query can fetch all that data at once.
This makes it particularly useful for mobile and SPA applications where bandwidth and latency matter.
GraphQL revolves around three main operations:
Although a GraphQL query resembles JSON, it is not JSON. One of its powerful features is that it allows clients to define what they want returned and in what format. This innovation fully addresses the issues of under-fetching and over-fetching.
{
user(id: "1") {
name
posts {
title
comments {
text
}
}
}
}
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}For example:
The above query fetches only the needed fields, making API calls lean and efficient.
Benefits:
Challenges:
For data fetching, GraphQL introduces a new paradigm that significantly improves upon previous methods.
When comparing GraphQL and REST, the two approaches to fetching data have distinct advantages and limitations. Understanding these key differences helps choose the right technology based on an application’s complexity and requirements.
With REST, you have multiple endpoints, which can lead to unnecessary time and data spent on over-fetching or under-fetching. With GraphQL, you can get a specific request and fetch it in one request.
This key difference enables GraphQL to be more efficient for modern applications that utilize nested and dynamic data structures. Server-defined endpoints do not constrain developers, as clients may be more involved in query construction.
Because of REST’s flexibility, GraphQL allows front-end developers considerable control over data flow, but confined endpoints are still a backend developer’s concern. Yet, flexibility comes with a price; unsophisticated and unrefined queries might contribute to server slowdown.
Even with that possible drawback, in simple use cases, due to its straightforward caching strategies and defined endpoint mapping, REST can be faster than GraphQL.
Certain HTTP methods and status codes dictate how and what to cache, making REST methods simple. In the GraphQL world, every single query request comes to a single endpoint, making caching more complex and requiring custom solutions.
This issue can be alleviated with tools like Apollo Client and Relay; however, the problem persists, particularly in large-scale use cases. Offer caching strategies.
When comparing the performance of GraphQL and REST, the key differences often revolve around how data is fetched and how efficiently the system can scale.
While both methods excel in different contexts, understanding how each handles large datasets, network efficiency, and response times is crucial to making the right choice for your application.
Let’s dive into how each performs under different scenarios.
When handling large datasets, both GraphQL and REST exhibit different strengths and weaknesses.
REST typically works by exposing multiple endpoints, each responsible for a specific resource—such as /users, /posts, or /comments. This setup is ideal for simple CRUD operations, but it becomes inefficient when applications need related or nested data.
For instance, displaying a user’s profile along with their posts and followers requires multiple REST calls, which increases network latency and load times.
With GraphQL, you can get all the associated data you need in one request. GraphQL understands exactly how to retrieve the data you request by combining elements that REST would keep apart.
This is particularly advantageous in mobile and low-bandwidth situations, as it helps lower the number of network requests.
However, GraphQL’s flexibility can sometimes become a double-edged sword. If clients request deeply nested or large data structures, servers can become overloaded, leading to slower response times.
Developers must implement query complexity analysis and depth limiting to prevent performance bottlenecks.
In short, REST works best with simple, smaller, and predictable patterns. On the other hand, GraphQL is more efficient with complex and interrelated data sets.
With REST, response times are typically fast and direct. This is achievable because every endpoint is fine-tuned to the specifics of data retrieval.
However, multiple requests can impact round-trip time because you have to request related information many times.
If your application requires a list of users along with their profiles and comments, you would need to make three separate requests using REST.
GraphQL simplifies things by allowing a single request, eliminating the need for multiple requests at once. This is particularly advantageous for mobile applications, given the limited bandwidth.
Moreover, GraphQL allows for batching and persisted queries, further enhancing speed and reducing the payload size.
REST still wins in scenarios where data caching is critical. Since GraphQL uses a single endpoint, HTTP caching mechanisms like ETags and 304 Not Modified responses are less effective.
GraphQL clients, such as Apollo, require extra work to enable custom caching, which involves additional storage maintenance.
GraphQL reduces latency on the client-side, which adds a need to fine-tune server performance. In contrast, REST is easier to manage. It provides predictable performance through systematic and uncomplicated caching.
To optimize REST APIs:
For GraphQL APIs:
Both approaches can achieve exceptional performance if implemented correctly, but GraphQL requires more careful monitoring and optimization due to its flexible query nature.
When choosing between REST and GraphQL, security is a critical factor to consider. Each approach presents unique challenges and opportunities, with REST being built on established protocols, while GraphQL’s flexibility requires additional layers of security to manage potential risks.
Understanding the security implications of both approaches will help ensure that your APIs are secure, efficient, and resilient to threats.
Generally, REST security is built around and facilitated by HTTP protocols and standards, so it is easier to implement. Common methods include:
REST’s structured, predictable endpoints are easier to protect and observe. Tools like Postman or Swagger provide easy testing environments for validating API security.
REST APIs can become exposed if endpoints are poorly managed, potentially leaking sensitive information through overly verbose error messages or other means lacking proper access control.
GraphQL introduces unique challenges because of its flexible query structure. Since clients can request almost any data combination, attackers can take advantage by sending deeply nested or expensive queries, overloading the server.
To combat this, developers use techniques such as:
With GraphQL, there is only one endpoint, and malicious activity monitoring can be exponentially complex. Conventional web application firewalls may struggle to understand the payloads, necessitating specialized GraphQL security.
Whether using REST or GraphQL, several universal security best practices apply—similar to making your website more secure against common vulnerabilities:
In sum, REST is the better option due to its advanced and proven security standards, which contrast with the complicated and specialized security challenges presented by GraphQL’s flexibility.
When choosing between REST and GraphQL, one of the key factors to consider is the development experience and available tooling.
REST’s longevity has allowed it to develop a robust ecosystem of tools, while GraphQL, being a newer approach, offers modern tools with a focus on flexibility.
In this section, we’ll explore the development tools and frameworks available for both approaches and how they impact the developer’s workflow.
REST is over twenty years old, which means it has an established development tools ecosystem along with development tools, frameworks, and best practices.
An experienced web development company will have extensive knowledge of REST, making it easier to find skilled developers and standardized solutions for your projects.
APIs for REST use tools like Swagger (OpenAPI), Postman, Insomnia, which all simplify the documentation and testing of REST APIs. Development frameworks like Spring Boot, Django REST Framework, or Express.js are built around REST and provide solid libraries for building RESTful services.
Since REST utilizes standard HTTP verbs and responses, it is easy to understand and use for developers. OpenAPI allows teams to document their APIs and promotes collaboration. Helps teams ensure API consistency, streamline endpoints, and optimize services.
The more static a REST API is, the more versions it typically has. Versioning is frequent due to structural changes in data, which can make it a tedious task.
This can sometimes become frustrating for front-end developers, as any changes or developments can only be made when the backend team is done.
GraphQL offers a modern web development experience with powerful tools like GraphiQL, Apollo Studio, and Hasura Console.
These tools allow developers to visually explore schemas, run queries, and debug in real time.
With GraphQL, front-end developers gain more independence—they can define the data shape they need without waiting for new endpoints. The strongly typed schema also provides automatic validation, reducing the risk of runtime errors.
Setting up GraphQL requires additional time and effort, as you need to create a schema, resolvers, and a type system. There are tools like Apollo Server and Nexus that abstract some of the work.
The understanding needed will still be much more advanced than what is needed for REST Developer Productivity and Learning Curve.
Due to its simplicity and ease of use, learning REST is relatively easy compared to GraphQL. Learning GraphQL is more advanced because it is more powerful, but it requires working with schemas, resolvers, and understanding complex query patterns.
However, once GraphQL is mastered, it proves to be an essential tool, especially for large-scale projects that require variable data.
Developers who have used REST and are trying GraphQL for the first time often say that GraphQL resembles a buffet, while REST is more like a set menu.
While both approaches have their advantage and are ultimately satisfying, the overall channelling of resources, control, and efficiency is handled quite differently.
Choosing between GraphQL and REST depends on the specific needs of your application. Both have unique strengths, and understanding when to use one over the other can lead to better performance and developer productivity
REST remains an excellent choice for:
For instance, a weather API or currency conversion service would be an excellent REST service, performing well due to its predictable functionality and ease of caching.
For applications that require real-time data, dynamic data fetching, and complex data structures, GraphQL is the perfect choice. The modern web and mobile applications built with frameworks like React, Vue, and Flutter are excellent use cases for GraphQL.
A good example would be Facebook’s news feed, which pulls and displays personalized data for each user. It requires lots of nested resources. GraphQL takes care of this specific complexity with very few data requests.
These days, many companies use a hybrid model, combining REST and GraphQL. For example:
Tools like Apollo Gateway or GraphQL Federation even allow REST services to be wrapped into a GraphQL schema, providing a smooth transition between both worlds.
To better understand the practical differences between REST and GraphQL, let’s look at how both can be implemented in a simple application.
We’ll walk through an example where a blogging platform retrieves a user’s profile, posts, and comments, demonstrating how REST and GraphQL handle the same task in different ways
To better distinguish between REST and GraphQL, let us consider an uncomplicated REST case. Suppose you have a blogging application and you want to retrieve a user’s profile, posts, and comments. In REST, this commonly involves several endpoints:
Here’s a REST-style example using Express.js:
// REST API Example
app.get(‘/users/:id’, (req, res) => {
const user = getUserById(req.params.id);
res.json(user);
});
app.get(‘/users/:id/posts’, (req, res) => {
const posts = getPostsByUser(req.params.id);
res.json(posts);
});
app.get(‘/posts/:id/comments’, (req, res) => {
const comments = getCommentsByPost(req.params.id);
res.json(comments);
});To display a complete profile with posts and comments, the client must make three separate HTTP requests, leading to extra latency and potential over-fetching of unnecessary data. While caching and pagination can optimize this, it still increases network overhead.
REST’s main advantage here is simplicity—each endpoint has a clear purpose and is easy to monitor. But as relationships between data grow more complex, the number of endpoints and requests multiplies, making REST less efficient for deeply nested data.
{
user(id: “1”) {
name
email
posts {
title
comments {
text
author {
name
}
}
}
}
}This single query fetches all required data—user details, posts, and comments—at once. Only the fields that were requested will be included in the response, neither more nor less.
GraphQL implementation on the server might look like this:
const typeDefs = `
type User {
id: ID!
name: String!
email: String!
posts: [Post]
}
type Post {
id: ID!
title: String!
comments: [Comment]
}
type Comment {
id: ID!
text: String!
author: User
}
type Query {
user(id: ID!): User
}
`;
const resolvers = {
Query: {
user: (_, { id }) => getUserById(id),
},
User: {
posts: (user) => getPostsByUser(user.id),
},
Post: {
comments: (post) => getCommentsByPost(post.id),
},
};GraphQL’s flexibility allows developers to add or remove data fields without changing the backend logic. This means front-end teams can evolve independently, leading to faster iterations and reduced coordination overhead.
| Feature | REST API | GraphQL API |
| Number of Requests | Multiple endpoints | Single endpoint |
| Data Control | Fixed responses | Fully customizable |
| Performance | Slower for nested data | Faster for complex queries |
| Caching | Built-in via HTTP | Requires manual implementation |
| Flexibility | Limited | High |
| Setup Complexity | Simple | Moderate to complex |
In summary, REST is straightforward and reliable but rigid, while GraphQL offers unparalleled flexibility and efficiency for complex data models.
Choosing between GraphQL and REST for mobile apps affects data efficiency, offline capabilities, and real-time updates. Each approach offers unique advantages depending on the app’s needs, particularly in terms of bandwidth usage, caching, and synchronization.
In mobile app development, data efficiency is crucial. Every kilobyte matters, especially for users on slow or limited networks. REST APIs often return unnecessary data that the app doesn’t require. This is over-fetching.
For instance, a REST endpoint that returns all user data may include fields such as address or preferences, even if the app only requires the user’s name.
GraphQL lets clients request only what they need, preventing over-fetching and improving the speed of data transmission.
Ultimately, user experience and load times will benefit. Mobile devices will consume less battery.
Additionally, fetching multiple resources is a time-saver due to the decrease in network calls. This is useful in services that operate in low-connectivity regions.
However, developers must carefully monitor query sizes to avoid unintentionally complex queries that could hurt performance.
For mobile apps, especially those used in remote areas, offline functionality is important. Because REST uses standard HTTP headers and ETags for caching, it streamlines the process to fetch and store data offline.
GraphQL requires more time and effort to set up, similar to Apollo Client and Relay, which offer normalized caching and enable offline access to previously fetched queries. This means users can store queries and reuse them offline.
This gives the developer more control, but more control also means more complexity with configuration.
The real difference lies in how caching is managed:
Thus, GraphQL provides superior customization, while REST offers plug-and-play reliability.
Modern mobile apps often demand real-time updates—think chat apps, notifications, or live dashboards. While REST can handle this using long polling or WebSockets, these methods can be cumbersome and bandwidth-heavy.
GraphQL, on the other hand, is easier to implement thanks to subscriptions, which allow the user to access real-time updates sent directly from the server. For instance, a chat server can send real-time notifications to users when new messages are sent.
GraphQL is the best option for apps that need instant, real-time synchronization, such as collaborative applications, multiplayer games, and live news feeds.
Although REST is dependable, it usually has more complexities than GraphQL to achieve the same quick responses.
While GraphQL is rapidly gaining traction, REST still holds strong in many enterprise environments. Understanding how companies use both technologies can shed light on industry adoption trends and future predictions.
Although GraphQL is gaining popularity, REST is still widely used in enterprise settings. Amazon, PayPal, and Twitter still use REST because of its ease, stability, and huge ecosystem support.
REST’s predictable nature and built-in caching make it ideal for large-scale, customer-facing APIs that demand reliability.
Many organizations prefer REST for public APIs, as it integrates well with existing security, documentation, and versioning systems. Tools like OpenAPI Specification have standardized REST documentation, making onboarding new developers seamless.
In contrast, GraphQL has been adopted by companies such as GitHub, Shopify, Netflix, and Airbnb to improve the experience for developers and the efficiency of data usage.
For example, GitHub replaced its older REST API with the GraphQL API v4, which allows developers to query multiple data sources in a single request.
GraphQL is also used internally by Netflix to streamline complex data-fetching between microservices for content recommendations, which are delivered across devices with low overhead.
These use cases demonstrate that the most innovative and fast-moving organizations, where data is in constant flux, derive the greatest benefits from GraphQL, as it reduces client-server requests, thereby improving speed and scalability.
The adoption curve for GraphQL is steeply rising. According to developer surveys, over 45% of modern startups now prefer GraphQL for new projects.
REST isn’t disappearing, but it’s evolving—many hybrid models use GraphQL as a query layer over REST endpoints, combining the best of both worlds.
In the coming years, we can expect:
Ultimately, the industry isn’t moving from REST to GraphQL—it’s learning how to use both strategically, based on the project’s goals and scale.
When choosing between GraphQL and REST, developers must weigh the trade-offs between flexibility, performance, and simplicity. Below is a summary comparison table, followed by an analysis of each approach’s benefits and challenges.
| Feature | GraphQL | REST |
| Endpoints | Single | Multiple |
| Data Fetching | Custom queries | Fixed responses |
| Performance (Nested Data) | High | Moderate |
| Caching | Custom (Apollo, Relay) | Built-in HTTP caching |
| Learning Curve | Steeper | Easier |
| Real-Time Support | Subscriptions | WebSockets/Long Polling |
| Security | Requires query control | Mature and stable |
| Tooling Ecosystem | Modern (Apollo, Hasura) | Mature (Postman, Swagger) |
| Versioning | Schema-based | URL-based |
| Use Case Fit | Dynamic UIs, mobile apps | Public APIs, microservices |
Use cases of GraphQL and REST should benefit developers. Choosing GraphQL provides query flexibility.
Developers must then specialize due to the need for caching and schema control. GraphQL zealots need to consider query security and the level of control they will implement.
The power of REST lies in its simplicity and predictability, which in turn fits well within well-defined services and stable infrastructures. Its existing downtime matches tools and protocols.
In the end, the trade-offs come to whether the developer will hit a flexibility wall, a performance wall, and, in real-time, a wall with REST. In terms of simplicity, scalability, and proven patterns, REST will be a solid choice.
The future of API development is shaped by the evolution of both GraphQL and REST, with innovations like GraphQL Federation and REST’s modernized specifications leading the way.
As growing companies grow, their APIs also become more abundant. Issues can arise quickly when trying to manage a single GraphQL schema across multiple microservices. GraphQL Federation and Schema Stitching can help to ease some of that burden.
GraphQL Federation, popularized by Apollo, allows developers to compose multiple GraphQL services into a single unified schema. Each microservice owns its part of the graph, making it easier to scale development across teams.
For instance, one team might manage the user schema, while another manages orders or products. The gateway then combines these seamlessly into one endpoint.
The older technique of Schema Stitching functions in some parallels, but in a more manual way. You can merge multiple schemas by explicitly constructing how fields in different APIs relate and connect.
Federation, however, is considered the evolution of this approach—it’s more scalable and fits perfectly into distributed systems.
This evolution demonstrates GraphQL’s adaptability. It’s no longer just a tool for startups; it’s a framework for enterprise-level API orchestration.
REST can’t match this level of schema composition or cross-service querying without complex workarounds.
In the future, expect more companies to adopt GraphQL Federation as they move toward microservice architectures, particularly for internal APIs that demand scalability and modular design.
While GraphQL continues to evolve, REST isn’t standing still. The community has developed modernized REST specifications, such as JSON: API and HAL (Hypertext Application Language), to address some of REST’s long-standing limitations.
JSON: API introduces a standardized way to structure JSON responses, reducing inconsistencies across different REST implementations. It supports compound documents, which can bundle related resources, somewhat mimicking GraphQL’s ability to fetch connected data efficiently.
Meanwhile, HAL specializes in hypermedia controls. It enables dynamic linking of resources via URLs. With this feature, REST APIs are discoverable and expose intelligent navigation to the clients.
Progress shows that REST is here to stay. It is adopting the lessons of GraphQL while maintaining its simplicity and stability.
The future of REST lies in standardization and smarter response design, ensuring that it continues to meet modern demands while retaining backward compatibility.
The short answer: No, but it will complement it.
GraphQL and REST are not competitors—they are solutions to different problems.
REST shines in scenarios requiring simplicity, caching, and compatibility with legacy systems. GraphQL excels when applications demand flexibility, real-time updates, and efficient data fetching.
In contemporary architectures, both GraphQL and REST are utilized simultaneously.
For example, GraphQL is used to communicate with the frontend and microservices. Meanwhile, REST is used to expose public APIs to third-party developers. This combination is becoming a common practice in the industry.
REST is part of the web’s foundation, while GraphQL is the next step in API development. The future lies in the combination of REST and GraphQL. Intelligent orchestration of APIs will utilize each strategy where it is most effective.
Choosing between GraphQL and REST isn’t about selecting the best option. It’s about aligning purpose with technology.
If there is a widely publicized REST, along with steady caching, and simple data works, it is still a reliable option.
REST works in predictable workflows and defined endpoints because of its well-established systems, method standardization, and scalability.
Nonetheless, when creating dynamic and data-heavy applications, such as dashboards, social networks, and e-commerce, no option will be as efficient.
Having a single endpoint, providing real-time data, and allowing customizable queries mean fewer complications for both end users and app developers.
Ultimately, the best API for a given project depends on the app’s complexity, the developers’ knowledge, and their vision for scalability.
For many developers, the best balance is achieved by using GraphQL and REST in tandem, with GraphQL providing flexibility while REST provides a structured backbone.
APIs are the core of all modern applications and will always be so. Although the complexity of the web will change, the quality of the API and the technology used will always remain the main priority.
1. What makes GraphQL faster than REST?
GraphQL reduces the number of network requests by retrieving all required data in a single query. It prevents over-fetching and under-fetching by allowing clients to request exactly what they need, improving speed and efficiency—especially for complex data models.
2. Is GraphQL more secure than REST?
Not by default. REST leverages long-standing and reliable security principles, whereas GraphQL introduces additional complexities, such as query depth restrictions and cost analysis, to limit overuse. Both systems can be extremely secure when properly configured.
3. Can I use GraphQL and REST together?
Of course! Numerous organizations integrate GraphQL on top of their existing REST APIs. This provides them with the stability of REST while giving them the versatility to use GraphQL for scenarios that require it.
4. Which is easier for beginners to learn?
For beginners, REST is the easier option. This is due to its simplicity and the extensive documentation. Learning GraphQL is challenging, but once mastered, it is more beneficial in the long run.
5. What lies ahead for API design beyond REST and GraphQL?
The next evolution in API design may focus on event-driven and real-time architectures, blending REST, GraphQL, and WebSockets for adaptive data communication. Technologies like gRPC and GraphQL Federation are paving the way for even more efficient, interconnected systems.
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