For most of my development career, REST was my only way of building APIs. It was what I learned first, and it stayed with me. I used it in different applications, including business applications, GIS platforms, dashboards, and e-commerce systems. REST felt natural because it was structured around resources, and the HTTP protocol made everything predictable.
I never really had a strong reason to explore GraphQL. It always felt like something that introduced extra level complexity and uncertainty without a clear benefit in a real production environment. That changed when I decided to rebuild part of an existing REST API using GraphQL, not as a replacement, but as an experiment to understand where it actually fits.
How REST Structures Systems
REST works by exposing resources through endpoints. In an e-commerce system, this typically looks like a clear separation of concerns across entities.
GET /products/100
GET /products/100/reviews
GET /products/100/related
GET /sellers/20
Each endpoint returns a specific dataset, and the frontend is responsible for combining them.
A simple product response might look like this:
{
"id": 100,
"name": "Wireless Headphones",
"price": 120,
"seller_id": 20
}
Then another request is required to fetch the seller:
{
"id": 20,
"name": "Tech Store",
"rating": 4.7
}
This structure works well because it is simple, explicit, and easy to debug. REST aligns strongly with business workflows where operations are clearly defined.
Where REST Starts to Show Limits
The challenge appears when frontend screens become more data-heavy. A single page in a modern application is rarely powered by a single endpoint. For a product page in an e-commerce system, the frontend may need product details, seller information, reviews, inventory, and related products.
With REST, this often becomes multiple sequential or parallel requests.
GET /products/100
GET /sellers/20
GET /products/100/reviews
GET /inventory/100
GET /products/100/related
The frontend is forced to merge these responses into one coherent view. On fast networks, this is manageable. On slower networks or mobile devices, it introduces latency and complexity in state management.
How GraphQL Changes the Model
GraphQL shifts the responsibility from multiple endpoints to a single query system. So Instead of the server deciding what each endpoint returns, the client defines exactly what it needs.
A GraphQL query for the same product page might look like this:
query {
product(id: 100) {
name
price
seller {
name
rating
}
reviews {
user
comment
rating
}
inventory {
quantity
warehouse
}
relatedProducts {
name
price
}
}
}
The response comes back in a single structured payload:
{
"data": {
"product": {
"name": "Wireless Headphones",
"price": 120,
"seller": {
"name": "Tech Store",
"rating": 4.7
},
"reviews": [
{
"user": "John",
"comment": "Very good quality",
"rating": 5
}
],
"inventory": {
"quantity": 34,
"warehouse": "Lagos Hub"
},
"relatedProducts": [
{
"name": "Bluetooth Speaker",
"price": 80
}
]
}
}
}
Instead of multiple requests, everything is resolved in one round trip.
Backend Structure Comparison
A REST controller typically looks like this:
@app.route("/products/<int:id>")
def get_product(id):
return get_product_by_id(id)
@app.route("/products/<int:id>/reviews")
def get_reviews(id):
return get_reviews_by_product(id)
In GraphQL, the structure shifts to types and resolvers:
class Product(graphene.ObjectType):
name = graphene.String()
price = graphene.Float()
seller = graphene.Field(Seller)
reviews = graphene.List(Review)
class Query(graphene.ObjectType):
product = graphene.Field(Product, id=graphene.Int(required=True))
def resolve_product(self, info, id):
return fetch_product_with_relations(id)
The important difference lies in how data relationships are modeled. REST separates concerns by endpoint. GraphQL models relationships directly inside the type system.
GIS Example Where GraphQL Becomes More Obvious
In GIS and land management systems, data is naturally relational. A single land parcel is connected to many entities.
With REST, this might require multiple endpoints:
GET /lands/100
GET /owners/25
GET /surveys/10
GET /documents?land_id=100
GET /transactions?land_id=100
With GraphQL, the same structure becomes:
query {
land(id: 100) {
parcelNumber
owner {
name
phone
}
survey {
surveyor
date
}
documents {
fileName
}
transactions {
amount
date
}
}
}
The response mirrors the real-world relationship between entities instead of forcing the frontend to assemble it manually.
Where GraphQL Does Not Replace REST
GraphQL is not designed for business operations. It is not ideal for workflows that involve state changes, validations, and side effects.
Actions like the following still fit REST better:
POST /orders
POST /login
POST /payments
POST /upload-document
POST /approve-transaction
These operations represent business intent rather than data retrieval. REST communicates that intent more clearly through HTTP semantics.
Protocol and Architectural Difference
REST is built directly on HTTP methods and resource-based URLs. Each endpoint represents a specific resource or operation, and caching is naturally supported at the HTTP layer.
GraphQL typically exposes a single endpoint:
POST /graphql
The complexity moves into the query layer. This flexibility allows precise data fetching but introduces challenges in caching, monitoring, and query optimization.
When GraphQL Is Worth It
GraphQL becomes valuable in systems where data is highly connected and frontend requirements change frequently. This includes dashboards, analytics platforms, GIS systems, social applications, and mobile apps that require aggregated data from multiple sources.
REST remains stronger in systems that are workflow-driven, transactional, and action-oriented.
Finally,
After working with both approaches, the conclusion is not that one replaces the other. It is that they solve different categories of problems. REST is better suited for business operations and system workflows. GraphQL is better suited for flexible data retrieval in highly relational systems.In most real-world architectures, the right answer is not choosing one over the other, but understanding where each one fits and combining them intentionally.
What’s your opinion? Let me know in the comments below, give a good read, like and share.
