GraphQL vs REST APIs -- The Case Against GraphQL

GraphQL vs REST APIs -- The Case Against GraphQL

GraphQL or REST APIs? The question is very important, and despite the former’s advantages or popularity, there are some disadvantages that you should consider, as this article shows.

Comparing GraphQL and REST APIs: The Case Against Adopting GraphQL

GraphQL, developed by Facebook, has emerged as a powerful alternative to traditional REST APIs. Its primary distinction lies in its flexible query language, allowing clients to request precisely the data they need. Structured hierarchically, data retrieval aligns with the required data’s shape, minimizing issues like over-fetching or under-fetching. This flexibility minimizes issues like over-fetching or under-fetching, making it particularly well-suited for applications with complex data relationships. Its operations include queries for data retrieval, mutations for modifying data, and subscriptions for real-time updates. It gained popularity for efficiently serving single-page applications (SPAs) and addressing the challenges posed by the REST architecture in scenarios where diverse data requirements are prevalent.

In contrast, REST has long been the accepted architectural style for creating online APIs. With a focus on resource-oriented design and stateless communication, REST makes use of common HTTP methods such as GET, POST, PUT, and DELETE. URIs serve as unique identifiers for resources, which can be stored in XML or JSON forms.

Representational State Transfer Application Programming Interfaces (REST APIs) are renowned for being straightforward and expandable. Every resource has its own endpoint, and CRUD actions correlate to specific HTTP methods. This design makes API structuring more approachable and widely used by enabling a clear and standardized approach.

In this article, we will be looking at:

  • The Fundamentals of GraphQl and REST APIs.
  • The advantages of GraphQl over REST API.
  • Challenges and Limitations of GraphQL.
  • Situations where REST remains preferable.
  • The overhead of transitioning to GraphQL.
  • Understanding the trade-offs between GraphQL and REST.

Fundamentals of GraphQL and REST APIs

In the dynamic landscape of web development, the debate between GraphQL and REST APIs often surfaces when considering how to architect data-driven applications. At the heart of this discussion lie the fundamental principles that shape how data is accessed, manipulated, and presented over the web. Representational State Transfer (REST) APIs have long been the cornerstone of web services, offering a standardized approach to building distributed systems. Meanwhile, GraphQL has emerged as a modern alternative, revolutionizing how clients interact with data by providing a more flexible and intuitive querying mechanism. Understanding their fundamentals is essential for developers aiming to build efficient and scalable applications. In this exploration, we’ll delve into the core concepts of these technologies, highlighting their strengths, weaknesses, and practical implications. Let’s briefly look at the fundamentals of GraphQL and REST APIs.


GraphQL is a runtime and query language for APIs that allows you to use your current data to execute queries. GraphQL supports three primary operations: Query, mutation, and subscription. Let’s examine these operations:

  • Queries GraphQL Queries are utilized to request data from the server.
query {
  user(id: "24680") {

This query requests data for a user with the ID “24680”. The client specifies its intent to retrieve the user’s name and email fields. This showcases GraphQL’s flexibility, allowing clients to tailor queries to fetch only the necessary data.

  • Mutation The Mutation is employed for modifying data on the server, such as creating, updating, or deleting resources.
mutation {
  createUser(input: { name: "Hannah", email: "" }) {

This mutation creates a new user, specifying the user’s name as “Hannah” and email as ”” The server responds with the newly created user’s ID, name, and other relevant data. Mutations in GraphQL manage operations that alter data on the server.

  • Subscriptions The Subscriptions operation establishes a real-time connection to the server to receive updates when specific events occur.
subscription {
  newPost {

This subscription establishes a real-time connection to the server to receive updates on new posts. Whenever a new post is created, the server sends the title and content to the client. Subscriptions are used for scenarios where real-time updates are required.


This network application design follows the REST architectural approach of representational state transfer. RESTful APIs adhere to a set of guidelines for developing scalable and maintainable web services. The principles are as follows:

  • Statelessness: Every request that a client sends to a server is fully equipped with all the necessary data to comprehend and handle the request. Between requests, the server does not keep track of the client’s status.
  • Client-Server Architecture: Separates the concerns between the client and the server, allowing them to evolve independently.
  • Uniform Interface: Defines a set of constraints to create a uniform and simplified communication style.
  • Layered System: REST embraces a layered system architecture, where different components (e.g., proxies, gateways) operate independently and interact through well-defined interfaces. This layered approach enhances scalability, flexibility, and security by encapsulating complexity and promoting modularity.
  • Resource-Based: Resources (entities or services) are identified by URIs, and the interactions are performed using standard HTTP methods (GET, POST, PUT, DELETE).

NOTE: GET is used to retrieve data. POST is used to create resources. PUT or PATCH are used to update resources. DELETE is used to delete resources.

Advantages of GraphQL Over REST

GraphQL has several benefits over conventional RESTful APIs, including its adaptable and effective approach to data retrieval. Selecting between these two can be made easier by being aware of these advantages and the situations in which they work well. Let’s examine a few of GraphQL’s advantages:

  • Efficient Data Retrieval By enabling clients to request just the data they require, GraphQL solves the over- or under-fetching issue that is frequently linked to REST. As a result, there is less needless data transit over the network and more effective data retrieval. In addition, its capacity to customize answers to individual requests boosts network efficiency and boosts application performance in situations where clients have varying and specialized data requirements.

  • Flexibility in Queries Flexible and dynamic inquiries are made possible by the client’s ability to choose the response’s structure. This adaptability is especially useful when the client’s data requirements vary or constantly change. For example, consider a scenario where a client application needs to display different sets of information about a user profile based on the user’s role or preferences. A REST API might require multiple endpoints or modifications to existing ones. With GraphQL, the client can dynamically request only the fields it needs for each specific view, reducing the need for multiple endpoints.

    GraphQL’s flexibility enables developers to adjust to changing requirements without the need for regular API modifications, which is particularly useful for applications with complicated data relationships or where client-side rendering requires a variety of data sets.

query {
  user(id: "user123") {
    # Additional fields based on client requirements
    # (client can choose which fields to include)
    posts {

In this query, the client can dynamically request fields like profileImage, bio, and posts based on the specific view it needs to render without needing to modify the server-side API.

  • Reduced Number of Requests By enabling the retrieval of various resources with a single query, GraphQL eliminates the requirement for several API requests. By doing this, the quantity of network requests is reduced, and overall efficiency is increased. Let’s consider a scenario where a client application needs to retrieve information about a user’s profile and their recent posts from separate database tables. A traditional RESTful API would require two separate API requests—one to fetch the user’s profile and another to fetch their posts. With GraphQL, the client can make a single query to fetch both sets of data in one go, reducing the number of network requests.

    Its ability to combine several queries into one is useful, improving performance in situations where lowering latency and optimizing data transfer are crucial.

query {
  user(id: "user123") {
    posts(last: 5) {

In this query, the client fetches the user’s profile information (such as name and email) along with their five most recent posts in a single request. This shows how GraphQL enables data retrieval from multiple tables with just one query, reducing the number of network requests and improving overall efficiency.

  • Versioning and Backward Compatibility: GraphQL’s robust type system simplifies the implementation of updates without disrupting existing clients. Requests for additional fields from clients won’t interfere with the operation of previous inquiries. Its schema evolution features offer a simplified solution for applications where preserving backward compatibility and introducing updates without upsetting current customers is crucial.

  • Real-time Data with Subscriptions: GraphQL supports real-time data changes via subscriptions. When particular data changes, clients can receive push alerts, providing real-time functionalities without the need for ongoing polling. Consider a chat application where users need to receive real-time updates when new messages are posted in a chat room. With GraphQL subscriptions, clients can subscribe to a specific query, such as newMessage, and receive instant notifications whenever new messages matching the query criteria are added. GraphQL’s subscription features provide a more effective and responsive solution than standard polling mechanisms in REST for applications that require real-time updates, like chat applications or collaborative editing platforms.

subscription {
  newMessage(roomId: "room123") {
    sender {

In this subscription query, the client subscribes to receive real-time updates for new messages posted in the chat room with the ID “room123”. Whenever a new message is added to this room, the client will receive push notifications containing details about the new message, such as its content, sender, and timestamp.

Challenges and Limitations of GraphQL

While GraphQL offers numerous advantages in terms of flexibility, efficiency, and improved client-server communication, it is not without its challenges and limitations. Understanding these challenges is essential for developers and organizations considering its adoption in their projects. Let us have a look at GraphQl’s limitations and issues.

  • Complexity in Implementation: The implementation of GraphQL can become complex as applications grow in sophistication. A key challenge lies in creating a well-defined schema. This entails carefully considering the data structure and relationships when selecting types, queries, and mutations. Moreover, attention must be paid to writing maintainable and efficient resolver routines. Ensuring consistency across resolver implementations becomes increasingly challenging as the schema evolves. This complexity could lead to code that is more difficult to understand and debug.

  • Performance Concerns: GraphQL addresses performance concerns by allowing clients to request only the necessary data. However, this flexibility can lead to issues such as over-fetching or under-fetching, where either too much or too little data is retrieved, potentially impacting system performance. Striking a balance between data retrieval efficiency and overall system performance can prove challenging. Another performance consideration is the N+1 query problem, which GraphQL may encounter if not managed properly. This issue arises when a single query triggers multiple database queries, potentially leading to performance bottlenecks. Effective management and optimization strategies are essential to mitigate the N+1 query problem and ensure optimal performance in GraphQL implementations.

  • Caching Difficulties: One of the challenges in GraphQL lies in caching due to its more stateful model, unlike REST, which benefits from a stateless nature that simplifies caching. Consequently, effective and reliable caching necessitates the implementation of robust global state management mechanisms. Additionally, maintaining cache validity proves to be a challenge in GraphQL systems. As data changes occur, it becomes difficult to ensure that the cache remains current. This challenge is further complicated by the requirement to develop subscription systems to notify clients of changes or to manually invalidate caches when necessary.

  • Security Considerations: Although clients can request specific fields, incorrect implementation may result in inadvertent data disclosure. To stop customers from accessing private data, queries must be validated and authorized. Also, malicious clients can create complex or highly nested searches that are computationally demanding, which might result in DoS attacks. It becomes imperative for security to implement depth restriction and query complexity analysis. In addition, employing safe procedures for user authentication and authorization is essential to prevent unwanted access to sensitive data, even though GraphQL itself does not mandate these methods.

Situations Where REST Remains Preferable

REST APIs continue to be a suitable choice in various scenarios, particularly when simplicity, statelessness, caching, limited bandwidth, and a mature ecosystem are critical factors.

  • Simple, Stateless Operations: REST APIs excel in scenarios involving straightforward, stateless processes where customers require prepared data sets and complex querying or hierarchical relationships are unnecessary. For instance, retrieving a list of products from an e-commerce platform can be efficiently handled: GET /api/products

  • Stateless Communication: REST APIs are suitable when maintaining client context between requests is unnecessary, and statelessness is a key requirement. For example, fetching weather information based on a location: GET /api/weather?location=city_name

  • Caching Requirements: In situations where HTTP caching methods are effective and straightforward to implement, REST APIs are preferable. For instance, retrieving static data such as country lists: GET /api/countries

  • Limited Bandwidth or Resources: REST APIs are advantageous when a lightweight communication method is needed to minimize data carried over the network, especially in environments with limited bandwidth or resources. For instance, mobile applications with bandwidth constraints may efficiently utilize REST APIs: GET /api/news?category=technology

  • Mature Ecosystem and Tooling: REST APIs are preferred in settings where they are supported by an established, stable ecosystem and tooling. This is particularly relevant when integrating with legacy systems or platforms that heavily rely on REST: GET /api/legacy/resource

In summary, for use cases prioritizing simplicity, common CRUD operations, statelessness, caching, bandwidth constraints, and leveraging a well-established ecosystem and tooling, REST remains the preferred choice over GraphQL. It’s essential to select the strategy that aligns best with the unique needs and limitations of the system or application.

The Overhead of Transitioning to GraphQL

Making the switch from REST to GraphQL has several expenses and resource concerns. Although GraphQL provides benefits in terms of adaptability and speedy data retrieval, the choice to switch should be carefully considered in light of the particular requirements and project restrictions. This section will cover the price and resource implications of switching from REST to GraphQL and assess if the switch is necessary given the particular requirements of a project.

Cost and Resource Implications

Understanding the various factors contributing to the overall impact of adopting GraphQL is crucial. These include the learning curve and training required, schema design and migration complexities, updates to client-side implementations, backend adjustments and resolvers, as well as performance considerations. Each of these elements plays a significant role in determining the resources, time, and effort needed to successfully integrate GraphQL into an existing system or build a new one. By addressing these aspects, you can better prepare for the transition to GraphQL and mitigate potential challenges along the way.

  • Learning Curve and Training: The GraphQL learning curve is one of the up-front expenses. It could take some time for team members to become used to the new ideas, query language, and subtleties of GraphQL, especially those who are used to REST. Developers may need to access training materials or other resources to become proficient in GraphQL.

  • Schema Design and Migration: Modifying or creating a new GraphQL schema can be an intricate and time-consuming procedure. Types, queries, mutations, and relationships must all be defined. Schema design and migration demand a committed effort from frontend and backend engineers. Although automated technologies can help, manual intervention is frequently required during the conversion process.

  • Updating Client-Side Implementations: Updating client-side implementations to support GraphQL queries is necessary, particularly for those that are closely connected to REST endpoints. This involves rewriting queries, updating data fetching logic, and adjusting components. Frontend development teams will spend considerable time refactoring and adapting code to make it compatible with GraphQL.

  • Backend Adjustments and Resolvers: Implementing resolvers for GraphQL queries and changes is required on the backend. The data access layer might need to be modified to take advantage of the flexibility that GraphQL provides. The creation and optimization of resolvers require time from backend engineers. This could entail changing the controllers, models, and database queries that are currently in use.

  • Performance Considerations: While GraphQL can offer performance benefits, improper implementation can lead to issues like the N+1 query problem. Optimizing queries and ensuring efficient data retrieval may require additional effort. Performance testing, profiling, and fine-tuning are essential tasks that may demand resources for analysis and improvements.

Transition Evaluation

The decision of this transition should be based on a careful evaluation of the project’s specific needs, scalability requirements, and the expertise of the development team. Considerations should include:

  • Complexity of Data Relationships: If the application involves complex data relationships and requires efficient data retrieval, GraphQL may justify the transition.
  • Scalability Requirements: GraphQL’s capacity to offer customized solutions can be helpful if the project expects to see significant growth and scalability is a top priority.
  • Flexibility in Client-Side Data Retrieval: If the project requires more flexibility in client-side data retrieval, GraphQL’s ability to request only the needed data can be a compelling reason to transition.
  • Existing RESTful APIs: The costs associated with switching to GraphQL may exceed the advantages if the present RESTful APIs are reliable, well-established, and able to handle the project’s demands without experiencing scalability issues.
  • Development Team Expertise: Assess whether the development team has the necessary skills and expertise to effectively implement and optimize GraphQL.

Understanding the Trade-offs between GraphQL and REST

Choosing between GraphQL and REST is not a one-size-fits-all decision, and understanding the trade-offs is crucial for making informed choices that align with the goals and constraints of a project. Here’s a balanced view, considering factors like team expertise, project scope, and long-term maintainability:

  • Flexibility vs. Convention: GraphQL provides clients with flexibility in data retrieval by enabling them to request only the information they require. This versatility may prove advantageous in intricate applications that demand several kinds of data. On the other hand, REST uses a more traditional methodology and has set endpoints, which makes it easier to use and more predictable. Ideal for applications with simple data relationships and conventional CRUD operations.

  • Team Expertise: Transitioning to GraphQL may present challenges and delays for developers, particularly those accustomed to REST, due to the learning curve involved. If the team lacks expertise in GraphQL, this transition could be particularly challenging. On the other hand, REST, with its familiarity and well-established nature, proves advantageous for teams with prior experience, ensuring smoother development and maintenance processes.

  • Data Fetching Efficiency: GraphQL optimizes data fetching by minimizing over- and under-fetching issues, particularly beneficial in scenarios where frontend clients have specific data requirements, thus enhancing efficiency. REST, with its standard endpoints, may encounter over-fetching or under-fetching problems. However, effective endpoint design and versioning can help alleviate these issues.

  • Network Efficiency: GraphQL minimizes the number of requests by enabling clients to specify the required data in a single query. This capability can lead to reduced bandwidth usage and improved network efficiency. On the other hand, with REST APIs, multiple requests may be necessary to retrieve related data. Although caching mechanisms can be utilized, careful design is required to prevent unnecessary data transfer.

  • Project Scope and Complexity: Suited for projects with complex data structures, relationships, and dynamic requirements, GraphQL shines in applications where data needs are diverse and may change over time. On the other hand, REST is well-suited for simpler projects with straightforward data models and relationships. RESTful APIs prove effective for projects that follow standard CRUD operations without extensive variations.

  • Tooling and Ecosystem Support: Expanding the ecosystem through the use of Relay and Apollo, GraphQL offers certain advantages. However, it’s worth noting that the REST ecosystem, being well-established, provides a wide range of tools and libraries for documentation, testing, and monitoring.

  • Long-Term Maintainability: For its adaptability to changing requirements, GraphQL potentially reduces the necessity for frequent API versioning. However, ensuring a well-designed schema is crucial for long-term maintainability. As for REST, its predictability and stability make it easier to maintain over time. Nonetheless, changes may necessitate versioning to prevent the disruption of existing client implementations.

  • Community and Documentation: The vibrant community surrounding GraphQL offers evolving best practices, supported by documentation tools like GraphQL Playground for ease of use. Conversely, REST boasts mature and well-documented standards complemented by extensive resources. Tools such as Swagger aid in generating clear API documentation.


In conclusion, GraphQL is not appropriate for every situation despite its strong advantages, which include flexible data retrieval and decreased over-fetching. The argument against its adoption highlights factors including the ecosystem’s maturity, the overhead of switching from REST, and the possibility of a learning curve for development teams. Representational State Transfer Application Programming Interface (REST API) remains a good option for projects with simple data requirements, especially when a traditional approach best fits the objectives and experience of the development team because of its simplicity, predictability, and well-established techniques. A thorough analysis of the project requirements, the available infrastructure, and the long-term maintainability of the selected API architecture should be used to inform the decision between GraphQL and REST.

Scale Seamlessly with OpenReplay Cloud

Maximize front-end efficiency with OpenReplay Cloud: Session replay, performance monitoring and issue resolution, all with the simplicity of a cloud-based service.