Falcon vs GraphQL: What are the differences?

### Introduction
When comparing Falcon and GraphQL, there are key differences that distinguish these two technologies.

1. **Data Fetching**: Falcon is a framework for building web APIs while GraphQL is a query language for APIs. Falcon follows a RESTful approach where clients access different endpoints to retrieve data. On the other hand, GraphQL allows clients to request only the data they need using a single endpoint and a specific query structure.
   
2. **Response Structure**: Falcon returns data in a predetermined structure defined by the API endpoints. In contrast, GraphQL allows clients to specify the structure of the response they need in the query, enabling more flexibility in the shape of the data returned.

3. **Overfetching and Underfetching**: With Falcon, overfetching or retrieving more data than necessary and underfetching or not getting enough data are common issues since clients have to make multiple requests to different endpoints. In GraphQL, overfetching and underfetching are minimized as clients can request exactly what they need in a single query.

4. **Versioning**: Falcon APIs often require versioning to manage changes in the API structure, leading to potentially breaking changes. GraphQL, on the other hand, allows for incremental changes without the need for versioning, providing a more flexible evolution of the API.

5. **Type System**: Falcon does not enforce any specific type system for defining data structures, which can lead to inconsistencies and errors. In contrast, GraphQL has a strong type system that helps ensure data consistency and validity, making it easier to understand and maintain the API.

6. **Performance Optimization**: Falcon APIs may suffer from performance issues when dealing with overfetching or underfetching due to multiple requests. With GraphQL, performance can be optimized by reducing the number of requests and fetching only the necessary data, leading to more efficient data retrieval.

In Summary, Falcon and GraphQL differ in their approach to data fetching, response structure, overfetching/underfetching issues, versioning strategies, type system enforcement, and performance optimization.