In the ever-evolving landscape of data engineering, building robust and efficient data APIs is a critical task. Choosing the right approach can significantly impact the performance, scalability, and flexibility of your data infrastructure. Two popular options for creating data APIs are RESTful and GraphQL. In this technical blog post, we’ll explore the strengths and weaknesses of each approach, providing insights to help you make an informed decision.

Understanding RESTful APIs

Representational State Transfer (REST) is an architectural style that has been widely used for designing networked applications. In the context of data engineering, RESTful APIs offer a structured way to interact with data. Each resource is represented by a URL, and a set of HTTP methods, such as GET, POST, PUT, and DELETE, are used to perform operations on these resources.

One of the key advantages of RESTful APIs is their simplicity and ease of understanding. They follow a predictable and intuitive structure, making them a great choice for beginners and simple use cases.

Example of a RESTful API Endpoint:

# Python Flask RESTful API
from flask import Flask, request
from flask_restful import Resource, Api

app = Flask(__name__)
api = Api(app)

class DataResource(Resource):
    def get(self, data_id):
        # Retrieve data with data_id

    def post(self):
        # Create a new data resource

    def put(self, data_id):
        # Update data with data_id

    def delete(self, data_id):
        # Delete data with data_id

api.add_resource(DataResource, '/data/<string:data_id>')

if __name__ == '__main__':

Pros of RESTful APIs for Data Engineering

  1. Statelessness: RESTful APIs are stateless, which means each request is independent. This makes them easy to scale and suitable for distributed systems.
  2. Caching: RESTful APIs work well with HTTP caching mechanisms, enhancing performance by reducing redundant requests.
  3. Uniform Interface: RESTful APIs provide a uniform interface, simplifying client integration and ensuring a consistent user experience.

Cons of RESTful APIs for Data Engineering

  1. Over-fetching/Under-fetching: Clients often receive more or less data than they need, which can result in inefficiency.
  2. Versioning: Handling API versioning can be challenging, especially as data structures evolve.
  3. N+1 Query Problem: Multiple round trips to the server may be required to gather related data, leading to performance issues.

Understanding GraphQL

GraphQL, on the other hand, is a query language for your API. It was developed by Facebook and open-sourced in 2015. GraphQL allows clients to request exactly the data they need, and nothing more, by specifying their data requirements in a single query.

Example of a GraphQL Query:

query {
  data(id: "123") {

GraphQL servers are designed to respond to these queries with precisely the requested data, minimizing over-fetching and under-fetching.

Pros of GraphQL for Data Engineering

  1. Flexible Data Retrieval: Clients can request only the data they need, reducing the risk of over-fetching and under-fetching.
  2. Simplified Versioning: GraphQL’s type system and introspection capabilities make versioning more manageable.
  3. Optimized for Mobile: GraphQL is ideal for mobile applications, where bandwidth and data usage are crucial.

Cons of GraphQL for Data Engineering

  1. Complexity: GraphQL APIs can become complex as the schema grows, making them challenging for newcomers to understand and maintain.
  2. Caching Challenges: Caching can be more complex in GraphQL, as queries can be highly dynamic.
  3. Performance Tuning: It requires careful consideration and optimization to prevent malicious or inefficient queries from affecting server performance.

Which One to Choose?

The choice between RESTful and GraphQL for data engineering largely depends on your specific use case. Here are some guidelines to help you make an informed decision:

  • Choose RESTful if:
    • You have simple data requirements.
    • You need a straightforward, well-understood structure.
    • Your project is starting small and growing gradually.
  • Choose GraphQL if:
    • You have complex data needs, and you want to minimize over-fetching and under-fetching.
    • You’re developing a mobile application where bandwidth and data efficiency are critical.
    • Your project requires flexible data access and evolves rapidly.

In conclusion, both RESTful and GraphQL have their strengths and weaknesses. The choice between them should be driven by the specific requirements of your data engineering project. RESTful APIs are simple and work well for many scenarios, while GraphQL excels in flexibility and efficient data retrieval. Your decision will have a significant impact on the success of your data infrastructure, so choose wisely.

By Abhishek K.

Author is a Architect by profession. This blog is to share his experience and give back to the community what he learned throughout his career.