GraphQL Basics for Beginners: What is It And Why to Use it?

Written by Andy in API Testing

Importance of APIs like GraphQL and REST in Modern Applications

In today’s connected world, APIs (Application Programming Interfaces) have become the backbone of software development. APIs are essential in enabling communication between different systems, devices, and applications, making data sharing seamless and efficient. They have revolutionized the way software is built, tested, and maintained, making it possible for developers to integrate various services and create feature-rich applications more quickly and easily. To learn more about the role of APIs in modern applications, check out this comprehensive guide on APIs Made Simple: What They Are and How They Work. In this article, we will focus on understanding GraphQL.

What is GraphQL?

GrahpQL-For-Beginners

Definition and Overview

GraphQL is a query language and runtime for APIs that enables developers to request and manipulate data more efficiently and flexibly. It was developed by Facebook in 2012 and released as an open-source project in 2015. The name “GraphQL” stands for Graph Query Language because it allows clients to traverse a graph of data and relationships between objects, similar to how graph databases work.

In contrast to traditional REST APIs, GraphQL allows clients to request only the data they need and nothing more, reducing the amount of redundant data being transferred over the network. It also enables clients to request multiple resources in a single request, which can help reduce the number of round-trips required to fetch data for complex applications.

GraphQL as a Query Language and Runtime

As a query language, GraphQL provides a syntax for clients to express their data requirements and shape the response returned by the server. This syntax is both human-readable and machine-readable, making it easy to work with and understand.

GraphQL also provides a runtime for executing these queries against a server’s data source. This runtime takes care of parsing and validating incoming queries, executing them against the underlying data, and formatting the response according to the requested shape.

GraphQL’s Role in API Development

GraphQL’s primary role in API development is to serve as an alternative to traditional REST APIs, addressing some of the limitations and inefficiencies associated with them. It allows developers to create more flexible, efficient, and maintainable APIs that are better suited to the needs of modern applications. GraphQL can be used with any backend technology or data source, making it a versatile solution for a wide range of use cases.

How is GraphQL different from REST?

Key Differences Between GraphQL and REST

There are several key differences between GraphQL and REST APIs that make them suitable for different use cases:

  1. Data Fetching: In REST, the server defines a fixed set of endpoints, each representing a specific resource or collection of resources. Clients have limited control over the data they receive, often leading to over-fetching or under-fetching of data. In contrast, GraphQL allows clients to request only the data they need, providing more control and flexibility in data fetching.
  2. Versioning: REST APIs often require versioning to accommodate changes in the data model or API functionality. This can lead to multiple versions of the same API and additional complexity in managing and maintaining them. With GraphQL, versioning is not necessary, as clients can request the data they need without affecting other consumers of the API.
  3. Single Endpoint: GraphQL APIs expose a single endpoint, through which clients can send queries and mutations to request and manipulate data. This is in contrast to REST APIs, which typically expose multiple endpoints for different resources and actions.
  4. Strongly-typed Schema: GraphQL APIs are built around a strongly-typed schema that describes the types, fields, and relationships between objects. This provides a clear contract between the client and server, making it easier to validate requests and responses, generate API documentation, and catch errors early in the development process. [Strongly Typed Schema – It’s like a strict librarian that only allows the books that fit within its pre-defined categories to be checked out. This ensures that the API returns only accurate and expected data, preventing errors and inconsistencies.]

Comparison of Data-fetching Approaches

In a REST API, clients fetch data by making requests to specific endpoints representing resources. These endpoints return a fixed structure of data, which may include more information than the client actually needs (over-fetching) or not include all the information required (under-fetching). To fetch additional data, clients often need to make multiple requests to different endpoints, which can lead to increased latency and reduced performance.

With GraphQL, clients have more control over the data they request, specifying exactly which fields and relationships they want to include in the response. This eliminates over-fetching and under-fetching, allowing for more efficient data fetching and improved performance. Clients can also request multiple resources in a single query, reducing the need for multiple round-trips to the server.

Examples to Illustrate the Differences

Let’s consider an example to illustrate the differences between REST and GraphQL when fetching data for a blog application.

With a REST API, you might have the following endpoints:

  • /posts to fetch a list of blog posts
  • /posts/:id to fetch a specific blog post
  • /authors/:id to fetch the author of a blog post

To fetch a list of blog posts along with their authors, a client would need to make multiple requests:

  1. Make a request to /posts to fetch the list of blog posts
  2. For each post, make a request to /authors/:id to fetch the author’s information

This approach can result in over-fetching (receiving more data than needed) and requires multiple round-trips to the server.

With GraphQL, a client could fetch the same data using a single query:

query {
  posts {
    title
    content
    author {
      name
      bio
    }
  }
}

This query explicitly specifies the required data (post title, content, and author’s name and bio), resulting in more efficient data fetching and a single round-trip to the server.

How does GraphQL help with data fetching and improve API performance?

Flexibility and Control Over Data Fetching

One of the primary benefits of GraphQL is its flexibility in data fetching. Clients can request exactly the data they need by specifying the fields and relationships they want to include in the response. This allows clients to tailor their requests to their specific needs, rather than relying on fixed endpoints and data structures provided by the server.

Avoiding Over-fetching and Under-fetching

In traditional REST APIs, over-fetching and under-fetching are common problems. Clients often receive more data than they need (over-fetching) or not enough data to fulfill their requirements (under-fetching). Both of these scenarios can lead to reduced performance and increased network overhead.

With GraphQL, clients can avoid these issues by requesting only the data they need. This reduces the amount of data transferred over the network and helps improve the overall performance of the API.

Real-world Performance Improvements

By allowing clients to request only the data they need and reducing the number of round-trips to the server, GraphQL can lead to significant performance improvements in real-world applications. These improvements can be especially noticeable in situations where network latency is high, such as mobile applications or slow internet connections.

What problems does GraphQL solve in service implementations and how?

Common Issues with REST-based Services

REST-based services can suffer from several issues that can make them challenging to maintain and evolve, including:

  1. Over-fetching and under-fetching of data, leading to reduced performance and increased network overhead
  2. The need for versioning to accommodate changes in the data model or API functionality
  3. The lack of a strongly-typed schema, making it difficult to validate requests and responses, generate documentation, and catch errors early in the development process

How GraphQL Addresses These Problems

GraphQL addresses these problems in several ways:

  1. Flexibility in Data Fetching: GraphQL allows clients to request only the data they need, avoiding over-fetching and under-fetching and improving API performance.
  2. No Versioning: GraphQL eliminates the need for versioning by allowing clients to request the data they need without affecting other consumers of the API.
  3. Strongly-typed Schema: GraphQL APIs are built around a strongly-typed schema that describes the types, fields, and relationships between objects. This provides a clear contract between the client and server, making it easier to validate requests and responses, generate API documentation, and catch errors early in the development process.

Benefits of Using GraphQL for Service Implementations

By addressing these common issues, GraphQL offers several benefits for service implementations:

  1. Improved Performance: By allowing clients to request only the data they need and reducing the number of round-trips to the server, GraphQL can lead to significant performance improvements in real-world applications.
  2. Easier Maintenance and Evolution: GraphQL’s flexible data fetching and lack of versioning make it easier to maintain and evolve APIs over time, reducing the complexity associated with managing multiple versions of an API.
  3. Stronger Contracts and Better Tooling: The strongly-typed schema used in GraphQL APIs enables better validation, documentation, and tooling, helping developers catch errors early and build more robust, maintainable APIs.

How is GraphQL Architecture Different from a REST-based Service?

GraphQL Schema and Type System

One of the key differences between GraphQL and REST is the schema and type system used in GraphQL APIs. In GraphQL, the schema defines the types, fields, and relationships between objects, providing a clear contract between the client and server. This strongly-typed schema makes it easier to validate requests and responses, generate API documentation, and catch errors early in the development process.

Queries, Mutations, and Subscriptions

In contrast to REST, which uses different HTTP methods (e.g., GET, POST, PUT, DELETE) to perform different actions on resources, GraphQL provides three primary operations for interacting with data:

  1. Queries: Queries are used to fetch data from the server. Clients can specify the shape of the response by including the fields and relationships they want to include in the result.
  2. Mutations: Mutations are used to modify data on the server, such as creating, updating, or deleting resources. Like queries, clients can specify the shape of the response to include any relevant data they need after the mutation.
  3. Subscriptions: Subscriptions allow clients to receive real-time updates when data changes on the server. This enables building real-time applications and features, such as notifications or live updates.

Data Fetching and Resolvers

In a GraphQL API, data fetching is handled by resolvers, which are functions responsible for fetching or modifying data from the underlying data source (e.g., a database, another API, or an in-memory data store). Resolvers are responsible for handling each field in the schema and can be customized to provide advanced functionality or optimizations, such as caching or batching.

When a client sends a query or mutation to the server, the GraphQL runtime processes the request, executes the appropriate resolvers, and returns a response shaped according to the client’s request.

Comparing GraphQL and REST Architectures

While both GraphQL and REST are approaches to building APIs, their architectures differ in several key ways:

  1. Data Fetching: In REST, clients fetch data by making requests to specific endpoints representing resources, with limited control over the data they receive. In GraphQL, clients have more control over data fetching, specifying the fields and relationships they want to include in the response.
  2. Schema and Type System: GraphQL APIs are built around a strongly-typed schema that describes the types, fields, and relationships between objects, providing a clear contract between the client and server. REST APIs do not typically have a strongly-typed schema, making it more difficult to validate requests and responses and catch errors early in the development process.
  3. Operations: GraphQL provides three primary operations (queries, mutations, and subscriptions) for interacting with data, while REST uses different HTTP methods (e.g., GET, POST, PUT, DELETE) to perform actions on resources. This distinction can make GraphQL more expressive and flexible in handling various data requirements.
  4. Single Endpoint: GraphQL APIs expose a single endpoint through which clients can send queries and mutations to request and manipulate data. This contrasts with REST APIs, which typically expose multiple endpoints for different resources and actions.
  5. Real-time Communication: GraphQL supports real-time communication through subscriptions, enabling the development of real-time applications and features. In contrast, REST APIs usually require additional mechanisms, such as WebSockets or polling, to achieve real-time communication.

Conclusion

GraphQL architecture offers more flexibility, control, and is less expressive (performance efficiency) than REST-based services, making it a powerful alternative for modern API development. By providing clients with the ability to request only the data they need, a strongly-typed schema, and support for real-time communication, GraphQL can help developers build more efficient, maintainable, and performant APIs. If you are more aware of testing SOAP or REST protocols, our comparison guide of REST vs SOAP vs GraphQL can help transition your understanding to the mindset shift while using GraphQL.

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