REST vs. GraphQL: Key Differences, Benefits, and Which One to Choose for Your Project

One of the key differences between junior and senior developers goes beyond just the ability to write code—since anyone can learn to code. It lies in the ability to make informed, strategic decisions. These decisions often involve evaluating trade-offs and selecting the most suitable tools for the task at hand. As a developer, it's crucial to understand various problem-solving approaches and choose the most effective solution. System design is fundamental for anyone aiming to be an exceptional developer. A common decision in system design is choosing between GraphQL and REST. When should you use each, and what are the advantages of each? This article will dive into these questions and guide you in selecting the best option for your next project.

Understanding the Architecture of REST and GraphQL: Key Differences Explained

REST Architecture

REST (Representational State Transfer) is an architectural style for designing networked applications, particularly web services. Its widely used for building scalable, stateless, and easy-to-understand web APIs.

REST leverages standard HTTP methods to interact with resources, which are entities identified by unique URLs. In a RESTful API, resources are defined and manipulated using HTTP methods such as GET, POST, PUT, and DELETE.

Three primary features underpin REST api Architecture:

1) Resource structure
2) HTTP Methods
3) Endpoint design

Let's say we are designing a social media application, we have resources like Posts, Comments, and Replies.

Resource Structure:

1. Posts: Represent social media posts.
2. Comments: Comments on posts.
3. Replies: Replies to comments.

HTTP Methods & Endpoints:

1. POST /posts: Create a new post.
2. GET /posts: Retrieve a list of posts.
3. GET /posts/{id}: Retrieve a specific post.
4. POST /posts/{id}/comments:Add a comment to a post.
5. GET /posts/{id}/comments: Get all comments for a specific post.
6. POST /comments/{id}/replies: Add a reply to a comment.
7. GET /comments/{id}/replies: Get all replies for a specific comment.

Refer to the diagram below for a clearer understanding of the rest api interaction with a database.

GraphQl Architecture

GraphQL presents a different approach compared to REST architecture, which operates on the principle of accessing resources through various HTTP methods at multiple endpoints. In contrast, GraphQL serves as a query language that enables users to request any type of data according to their specific needs. The fundamental idea behind GraphQL is that the client constructs a query detailing the required data and sends it to the API using an HTTP POST request. Unlike REST, all GraphQL queries are directed to a single endpoint via the POST method.
Two primary features underpin GraphQL:

1. Schema: This defines the different data types, including posts, comments, and replies.
2. Queries and Mutations: Most GraphQL schemas incorporate a query section that specifies the types of queries permissible for the API. Instead of relying on HTTP methods for creating, editing, or deleting resources, GraphQL utilizes queries for data retrieval (such as posts, comments, and replies) and mutations for data modifications (like creating posts or adding comments and replies). This structure allows for more efficient and flexible data interactions compared to traditional RESTful services.

Refer to the diagram below for a clearer understanding of a graphql api interaction with a database.

From the overview this are the key differences

Aspect	GraphQL	REST
Definition	A query language and runtime for APIs that allows clients to request exactly the data they need.	An architectural style for APIs where clients request data through multiple HTTP endpoints.
Data Request	Single endpoint to handle all operations (POST). Multiple requests may result from the server fetching nested or related data.	Multiple endpoints (GET, POST, PUT, DELETE) for different resources.
Efficiency	Reduces the number of network round-trips by allowing nested queries.	Multiple requests are often needed to retrieve related data, leading to more network overhead.
Query Language	Uses a single, flexible query language that can describe complex and nested queries.	Follows standard HTTP methods and routes, which require separate requests for nested data.
Response Size	Smaller responses due to efficient fetching of only necessary fields.	Larger responses due to over-fetching or under-fetching of related data.
Scalability	Efficient with complex, nested structures. Reduces server workload.	Can be less scalable if many separate requests are required.
Client Requests	One client request can retrieve multiple related resources in a single call.	Multiple HTTP requests required for related resources, often increasing latency.
Structure	A single endpoint (usually POST) handling all operations.	Multiple endpoints (GET, POST, PUT, DELETE) based on resource type.
Data Fetching	Can fetch only the exact fields needed, reducing data size and overhead.	Can result in over-fetching or under-fetching, leading to unnecessary network traffic.
Code Complexity	Simplifies client-side operations by allowing nested queries and precise field selection.	Requires multiple requests for nested or related data, making client code more complex.
Performance	Faster for complex queries and nested data due to reduced number of requests.	Slower with multiple requests for related data, potentially increasing latency.
Maintenance	Easier to maintain due to the flexibility of the query language and single endpoint.	Can require more maintenance with multiple endpoints for different resources.
Error Handling	Errors can be handled more specifically within a single query.	Errors need to be handled separately for each endpoint.
Versioning	No need for versioning as the schema can be updated without breaking client operations.	Versioning may be required due to changes in endpoints and data structure.
Client Flexibility	More flexible for clients to specify exactly what data they need.	Client flexibility limited by predefined endpoints and response structures.

Thank you for reading through this article. I hope it was helpful.