TechnicalPig🐷: GraphQL vs RESTful API

Introduction to GraphQL

GraphQL is a query language for your API for executing queries by using a type system you define for your data.

Unlike REST which is an architectural style, GraphQL is a specification. An architectural style is a high level framework that guides how software should interact with each other. On the other hand, a specification defines the exact requirements and expectations of how something should operate.

This means that GraphQL provides a detailed description of how clients should request data and how servers should respond to those requests.

Querying in GraphQL

In GraphQL, your data is represented as a graph - not in the visual sense, but a concept of interconnected data. Entities (nodes) are connected to each other through relationships (edges). For example, in a social networking application, users, post and comments could be nodes in the graph, with edges representing the relationship between them (e.g. a user creates posts, posts have comments). A single query can traverse this graph to fetch a complex set of related data such as a user, all their posts and all the comments for the post in one go.

GraphQL is agnostic about how data is stored. It is a query language for executing those queries against your data. The GraphQL server is responsible for translating GraphQL queries into operations that fetch data from your storage system, respecting the graph of data described by the GraphQL schema.

Benefits of GraphQL

• Fine-grained Data Retrieval: Allows clients to request exactly the data they need. This eliminates the problems of over-fetching and under-fetching that are common in RESTful services.

• Single Endpoint: GraphQL APIs typically operate from a single endpoint. This simplifies the structure of your API and can reduce the number of network requests needed to fetch complex data.

• Real-time Data with Subscriptions: Supports real-time updates through subscriptions, making it ideal for applications that require real-time data (e.g., chat applications, live updates).

• Strongly Typed Schema: The schema defines the capabilities of the API and specifies the data format. This can improve developer productivity and tooling support, with features like automatic documentation, validation, and type checking.

Drawbacks of GraphQL

• Caching Complexity: Caching is more nuanced in GraphQL due to its single endpoint - because the cache cannot simply key off the URL and HTTP method since they are the same for every requests.

• Mutation Testing: Testing mutations (operations that create, modify, or delete data) can be complex as it requires understanding the impact on the entire data graph. For example, deleting a user might require removing their posts. A test must verify not just the immediate outcome of the mutation but also its impact on related data.

• Performance Considerations: Complex queries can potentially lead to performance issues. Because GraphQL allows clients to craft queries that are deeply nested or require data from multiple sources, the server might need to perform complex operations to fulfil these requests. Efficiently resolving queries, especially those that require fetching data from multiple sources, can be challenging.

Comparison with RESTful APIs

• Schema type: The concept and enforcement of schemas in REST are not as intrinsic or strictly defined as in GraphQL. In REST, we can use libraries like Zod to create schemas for validation and documentation.

• Data Fetching: REST typically requires loading from multiple URLs to gather all the necessary data. Without proper control, this can lead to over-fetching or under-fetching. GraphQL, however, allows for more precise data fetching in one go.

• Versioning: REST APIs often introduce new versions over time, leading to versioning complexity. GraphQL reduces this need by allowing new fields to be added to responses without impacting existing queries.

• Caching: REST benefits from the built-in HTTP caching mechanisms, which can be more straightforward than implementing caching in GraphQL. GraphQL requires more sophisticated client-side or server-side caching solutions.

• Flexibility vs. Simplicity: GraphQL offers more flexibility in querying and mutations, ideal for complex systems and microservices. However, this comes at the cost of higher complexity compared to the simplicity and convention-based approach of RESTful APIs.

Making the Architectural Decision

When deciding between GraphQL and RESTful APIs, consider the specific needs of your project:

• Complexity of Data Retrieval: if your application needs to aggregate large amounts of data from various sources efficiently, GraphQL offers a powerful and flexible approach to fetch data efficiently. However, it requires careful consideration and optimisation to ensure that complex queries do not degrade performance.

• Real-time Data Requirements: GraphQL might be preferable for applications requiring real-time updates.

• Team Familiarity and Ecosystem: REST may be a better choice if your team is more familiar with RESTful principles and if the ecosystem of tools around REST fits your needs better.

• Performance and Scalability Needs: Assess the nature of your queries and the potential performance implications. GraphQL offers powerful querying capabilities but requires careful consideration of query optimisation and server load.