Comparing REST and GraphQL - AWS AppSync GraphQL

Comparing REST and GraphQL

APIs (Application Programming Interfaces) play a crucial role in facilitating data exchange between applications. As stated earlier, two prominent approaches for designing APIs have emerged: GraphQL and REST. While both serve the fundamental purpose of enabling client-server communication, they differ significantly in their implementation and use cases.

GraphQL and REST share several key characteristics:

  1. Client-Server Model: Both use a client-server architecture for data exchange.

  2. Statelessness: Neither maintains client session information between requests.

  3. HTTP-Based: Both typically use HTTP as the underlying communication protocol.

  4. Resource-Oriented Design: Both design their data interchange around resources, which refer to any data or object that the client can access and manipulate through the API.

  5. Data Format Flexibility: JSON is the most commonly used data exchange format in both, though other formats like XML and HTML are also supported.

  6. Language and Database Agnostic: Both can work with any programming language or database structure, making them highly interoperable.

  7. Caching Support: Both support caching, allowing clients and servers to store frequently accessed data for improved performance.

While sharing some fundamental principles, GraphQL and REST differ significantly in their approach to API design and data fetching:

  1. Request Structure and Data Fetching

    REST uses different HTTP methods (GET, POST, PUT, DELETE) to perform operations on resources. This often requires multiple endpoints for different resources, which can lead to inefficiencies in data retrieval. For example, running a GET operation to retrieve a user's data may lead to data over-fetching or under-fetching. To get the correct data, truncation or multiple operations may be called.

    GraphQL uses a single endpoint for all operations. It relies on queries for fetching data and mutations for modifying data. Clients can use queries to fetch exactly the data they need in a single request, which reduces network overhead by minimizing data transfer.

  2. Server-side Schema

    REST doesn't require a server-side schema, though one can be optionally defined for efficient API design and documentation.

    GraphQL uses a strongly-typed server-side schema to define data and data services. The schema, written in GraphQL Schema Definition Language (SDL), includes object types and fields for each object and server-side resolver functions that define operations for each field.

  3. Versioning

    REST often includes versioning in the URL, which can lead to maintaining multiple API versions simultaneously. Versioning is not mandatory but can help prevent breaking changes.

    GraphQL promotes a continuous evolution of the API without explicit versioning by requiring backward compatibility. Deleted fields return error messages, while deprecation tags phase out old fields and return warning messages.

  4. Error Handling

    REST is weakly typed, requiring error handling to be built into the surrounding code. This may not automatically identify type-related errors (e.g., parsing a number as text).

    By contrast, GraphQL is strongly typed and requires a comprehensive schema definition. This allows your service to automatically identify many request errors with a high level of detail.

  5. Use Cases

    REST is better suited for:

    • Smaller applications with less complex data requirements.

    • Scenarios where data and operations are used similarly by all clients.

    • Applications without complex data querying needs.

    GraphQL is better suited for:

    • Scenarios with limited bandwidth, where minimizing requests and responses is crucial.

    • Applications with multiple data sources that need to be combined at a single endpoint.

    • Cases where client requests vary significantly and expect different response structures.

    Note that it's possible to use both GraphQL and REST APIs within a single application for different areas of functionality. Furthermore, you can upgrade a RESTful API to include GraphQL capabilities without a complete rewrite. See How to build GraphQL resolvers for AWS data sources for an example.