Answer These Questions to Pass Your GraphQL Interview

  • 23 Oct, 2023
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A Comprehensive Guide to GraphQL: Answering Key Interview Questions

In recent years, GraphQL has gained considerable popularity as a powerful tool for building APIs. In this article, we will explore the fundamental concepts of GraphQL and provide detailed answers to common interview questions. Let’s dive into the fascinating world of GraphQL!

What is GraphQL?

GraphQL is an open-source query language and runtime for APIs developed by Facebook. It enables clients to request specific data structures and minimize over-fetching or under-fetching of data. Unlike traditional REST APIs, GraphQL allows clients to specify exactly what data they need, reducing the number of round trips to the server.

What is GraphQL used for?

GraphQL is used for creating efficient and flexible APIs that can be easily consumed by various client applications, such as web and mobile. It enables developers to build declarative APIs, allowing clients to request multiple resources in a single request and providing predictable responses. GraphQL is widely adopted by companies like Facebook, GitHub, and Shopify to improve their data fetching capabilities.

What Advantages are there for using GraphQL

a. Efficient and declarative queries: Clients can request precisely the data they need, avoiding over-fetching or under-fetching issues.

b. Reduced number of API round trips: GraphQL enables clients to gather data from multiple resources in a single request, enhancing performance and reducing network overhead.

c. Strong typing and validation: GraphQL schemas provide a structured and self-documenting interface. This leads to better collaboration between frontend and backend teams and helps prevent common API integration errors.

d. Versioning and backward compatibility: GraphQL supports schema evolution, allowing the addition of new fields and types without breaking existing clients. This ensures smooth backward compatibility.

What are the Disadvantages of using GraphQL

a. Caching complexity: Due to its flexibility, GraphQL doesn’t inherently provide built-in caching mechanisms. Implementing caching strategies requires additional effort from developers to achieve optimal performance.

b. Increased payload size: While GraphQL reduces over-fetching, it can increase payload size compared to REST APIs. This is because clients receive only the requested data, including all nested fields, which may lead to larger responses.

c. Learning curve: GraphQL introduces new concepts and patterns, which may require developers to invest time and effort in understanding and learning how to effectively use the technology.

How does GraphQL differ from traditional REST APIs?

a. Data-fetching granularity: GraphQL allows clients to specify the exact data they need in a single request, which minimizes the number of API round trips. In contrast, REST APIs often rely on multiple endpoints or complex query parameters to retrieve related data.

b. Versioning and backward compatibility: GraphQL provides native support for schema evolution, allowing smooth upgrades without breaking existing clients. REST APIs often require versioning through URL prefixes or query parameters.

c. Structured responses: GraphQL responses adhere to a pre-defined schema, making it easier for clients to understand and consume the data. REST APIs typically offer more flexibility but may require additional effort from clients to integrate new changes.

How do you set up a GraphQL server?

To set up a GraphQL server, we can use popular frameworks like Apollo Server or Express with GraphQL middleware. Here’s a basic example using Apollo Server and Node.js:

// Import required packages
const { ApolloServer, gql } = require('apollo-server');

// Define your GraphQL schema
const typeDefs = gql`
  type Query {
    hello: String

// Define your resolvers
const resolvers = {
  Query: {
    hello: () => 'Hello, GraphQL!',

// Create an instance of ApolloServer
const server = new ApolloServer({ typeDefs, resolvers });

// Start the server
server.listen().then(({ url }) => {
  console.log(`GraphQL server running at ${url}`);

How do you write a GraphQL query?

GraphQL queries define the structure of the data we want to fetch from the server. Here’s an example of a query to fetch a user’s name and email:

query {
  user(id: "123") {

How do you protect query types?

To protect query types and ensure that only authorized users can access sensitive data, we can implement authentication and authorization logic in our GraphQL server. This can be achieved by using middleware or directives provided by GraphQL frameworks like Apollo Server.

Connecting GraphQL to a database

a. SQL databases: We can connect GraphQL to SQL databases using ORMs (Object-Relational Mappers) like Sequelize or TypeORM. These ORMs provide mechanisms to define models, query the database, and map the results to GraphQL types.

b. NoSQL databases: For NoSQL databases like MongoDB, we can use libraries like Mongoose or Prisma to define schemas, interact with the database, and expose the data through GraphQL API endpoints.


In this article, we have covered the fundamental concepts of GraphQL and provided detailed answers to key interview questions. We explored what GraphQL is, its advantages and disadvantages compared to REST APIs, and how to set up a GraphQL server. We also discussed query writing, protecting query types, and connecting GraphQL to both SQL and NoSQL databases. GraphQL’s flexibility and efficiency make it an excellent choice for building modern APIs that cater to the specific needs of client applications.