GraphQL vs REST: Choosing an API Architecture

Published: 2023-05-02

1. Overview

An API Architecture is a system designed to expose the back-end data and/or functionality of an application for use in other applications, websites, or services. This allows developers to create multiple applications and user experiences from the same set of reusable components, which can improve security and reliability by reducing the number of ways your applications interact with data.

There are two leading frameworks for developing your API architecture: Representational State Transfer (REST) and the GraphQL ecosystem. REST is a well-established architecture that uses HTTP methods to interact with resources, while GraphQL is a newer approach that uses a single endpoint and a query language to retrieve data. Each comes with its own set of advantages and disadvantages, and choosing the right one for your use case can have a significant impact on the performance, scalability, and usability of your application.

2. What is REST?

REST is a set of architectural principles and guidelines for building scalable web services. It defines a scalable approach for communications between networked applications.

Resource Identification and Verbs

In a RESTful architecture, resources are identified by URLs and communication is based on the HTTP specification.

A collection of a particular type of resource might be defined at location /collection, with sub resources located at /collection/subresource.

The HTTP standard methods, including POST, GET, PUT, and DELETE, define the actions that can be taken upon resources. These four in particular represent the standard CRUD actions of create, read, update, and delete.

By sending HTTP standard requests to defined resources, a client is able to act upon these resources in a uniform manner.

Statelessness

In REST, each request from the client to the server must contain all the information necessary to process the request. The server does not store client state.

Evolvability

RESTful APIs are able to evolve over time without breaking client implementations. New resources, fields, or operations can be added withou affecting excisting clients as long as backwards compatability is maintained, along iterative evolution of APIs.

3. What is GraphQL?

GraphQL is an open-source query language and runtime for APIs developed by Facebook. It was designed to address some of the perceived limitations and inefficiences of traditional REST APIs by providing a flexible approach to requesting and manipulating data.

Strongly Typed Schemas

GraphQL APIs have a schema that deffines all available types of data and the relationship between them. The schema servces as the contract between the client and server. As the schemas are strongly typed, requestscan be automatically validated, providing quick feedback to clients about potential errors.

Client-Defined Hierarchical Queries

Clients can specify the structure of the response by constructing queries with nested fields, allowing the to avoid overfetching or underfetching data. GraphQL allows clients to define the shape of the response they desire.

Extensibility

GraphQL schemas are highly extensible and allow developers to add new types and fields without breaking existing queries, and therefore existing clients. This allows the gradual evolution of APIs.

4. Pros and Cons of REST

Pro: Widespread Adoption

Since its introduction in Roy Fielding's doctoral disseration in 2000, REST has become the domninat choice for building scalable, distributed systems. This has lead to wide support amongst development frameworks and libraries, adoption by major platforms, and robust tooling and documentation.

Pro: Interoperability

REST's use of standard HTTP methods, status codes, and content types promotes interoperability between systems. This allows REST to be platform and language agnostic, as clients and servers implemented in vastly different technologies can communicate and understand each other.

Pro: Scalability

REST's statelessness and uniform interface enable horizontal scaling. As client state is not saved on the server, RESTful APIs can handle large numbers of concurrent requests, making them appealing for high-demand applications.

Pro: Flexibility

As REST is a set of architectural guidelines and principles and not a technology in and of itself, it is highly flexible. REST can accommodate multiple formats for data representation -- such as XML, JSON,and even HTML -- and allows API developers to define the the structure of those payloads as well as the path of the Uniform Resource Identifiers (URIs).

Con: Potential Overfetching and Underfetching

Overfetching happens when an API endpoint returns more data than a client needs because the payload returned by the server includes additional fields or resources the client did not request or does not care about. Underfetching is the opposite -- an API endpoint may not return all the data a client needs, forcing it to make additional requests.

Mechanisms like using query parameters to filter or expand data can help overcome this, but can increase the complexity of the implementation and decrease a client's ability to understand how to use it.

Con: Multiple Request Overhead

Often in REST implementations a client must make multiple requests to API endpoints to fulfill a single task or retrieve related data. This creates overhead in the form of the round trips required for each request -- establishing a connection, sending the request, and awaiting the response.

This can lead to increased network traffic, resource utilization, system latency, and code complexity. Thoguh some of this may be mitigated by employing strategies such as caching, batching of API calls, and data denormalization (including related data in a single response).

5. Pros and Cons of GraphQL

Pro: Efficient Data Fetching

GraphQL is a declarative query language, meaning tha tclients express the data they want. This gives the GraphQL server the ability to optimize data queries and fetch data efficiently for the client. This hopefully reduces the number of API or database calls the GraphQL server needs in order to fulfill the client's data request.

Pro: Reduced Network Overhead

GraphQL allows a client to specify all of the data it needs in a single request along with the fields it would like returned. This limits the number of requests a client needs to make and minimizes the size of the payloads transferred over the network.

Pro: Self-Documenting API

The strongly typed schema a GraphQL API acts as the contract for client and server and is the single source of truth for data availability and request validation. Extending the API necessarily requires updating the schema, providing strongly typed documentation to consuming clients.

Con: Learning Curve

Implementing a GraphQL server requires a different approach compared to traditional RESTful APIs. Developers need to understand how to define and configure a GraphQL schema, handle resolvers to fetch data, and optimize data fetching strategies. This shift in mindset and development practices may initially pose challenges for teams accustomed to RESTful API development.

Additionally, GraphQL has its own query language, which differs from traditional RESTful API syntax. Client developers need to learn the GraphQL query language, including its syntax, query structure, and features like aliases, fragments, and variables. This can require some adjustment for developers who are more familiar with RESTful API conventions.

Con: N+1 Issues

Like many queries, GraphQL is susceptible to the N+1 problem, which occurs when a single GraphQL query triggers multiple database or API calls. If not properly addressed, this can lead to performance issues, as each additional request introduces latency and consumes resources.

Con: Caching Challenges

Caching in GraphQL can be more challenging compared to traditional RESTful APIs due to the fine-grained nature of queries and varying client requirements. Determining caching strategies, cache invalidation mechanisms, and striking the right balance between real-time data needs and cache utilization can be complex. Implementing caching at different layers, including the client, CDN, and server, can help mitigate performance issues, but increases the complexity of caching and invalidation.

Con: Large Network Payloads

While GraphQL reduces over-fetching, it's still possible for clients to request large amounts of data in a single query. This can result in large network payloads and increased network transfer times, as well as large amounts of load on GraphQL server. Clients and servers should consider strategies like pagination, field selection, and compression to minimize network payload size and improve performance.

6. Comparing REST and GraphQL

Learning Curve

GraphQL: Introduces new concepts and a specific query language, which may require developers to invest time in understanding and learning these aspects.
REST: RESTful APIs follow familiar conventions and use HTTP methods, which are widely understood by developers. The learning curve for REST is generally lower compared to GraphQL.

Network Overhead

GraphQL: Reduces network overhead by allowing clients to request only the specific data they need, minimizing over-fetching and reducing payload size. It supports efficient data transfer and reduces the number of network round trips.
REST: RESTful APIs may involve over-fetching or under-fetching of data due to the fixed structure of endpoints, potentially leading to increased network overhead and larger payload sizes.

Performance

GraphQL: GraphQL can face performance challenges such as the N+1 problem, inefficient resolvers, and complex queries. However, with proper optimization techniques like batching, caching, and query analysis, these challenges can be mitigated.
REST: RESTful APIs can also face performance issues, such as the need for multiple requests to retrieve related data and potential over-fetching. However, REST APIs have been in use for a longer time, and there are established best practices and performance optimization techniques available.

Documentation

GraphQL: GraphQL APIs provide self-documenting capabilities as the schema itself serves as comprehensive documentation. The strong typing, field descriptions, and introspection support aid in understanding the API structure and capabilities.
REST: RESTful APIs typically require separate documentation to describe the available endpoints, request/response formats, and supported operations.

Ecosystem and Tooling

GraphQL: GraphQL has a growing ecosystem with various tools, libraries, and frameworks available for development, documentation generation, and performance optimization. However, the evolving nature of the ecosystem may require developers to stay updated with new releases and tools.
REST: RESTful APIs have a mature ecosystem with well-established tools, frameworks, and documentation resources. The availability of extensive tooling and best practices can simplify development and integration tasks.

7. When to use REST vs GraphQL

The decision to use GraphQL or REST depends on the specific needs and requirements of your project.

Use GraphQL:

If clients have varying data needs and require precise control over the data they receive, GraphQL's ability to request specific fields makes it a good fit.
If you want to minimize network overhead by fetching only the required data and avoid over-fetching or under-fetching.
If your application needs to aggregate data from multiple sources or microservices, GraphQL's ability to unify and fetch data from various backends can be advantageous.

Use REST:

If simplicity and ease of understanding are key factors.
If caching plays a critical role in your application's performance, REST's cache-friendly nature can be advantageous.
If your project already has an established RESTful infrastructure, including tools, frameworks, and documentation.
If your project aligns with a resource-oriented architectural style, REST may be a natural choice.

It's important to note that these are general guidelines, and the decision should be based on the specific requirements, team expertise, and long-term goals of your project. It's also possible to use a combination of both approaches, with GraphQL for specific parts of the application and REST for others, depending on the needs of each use case.

Categories: apis software development