GraphQL: How JavaScript Clients Query and Cache Data

This article provides an overview of GraphQL, detailing what it is and how it fundamentally differs from traditional REST APIs. It then explains how modern JavaScript clients execute queries to retrieve structured data and leverage normalized client-side caching to boost web application performance and maintain consistent state across components.

What is GraphQL?

GraphQL is an open-source query language for APIs and a runtime for fulfilling those queries with existing data. Developed by Facebook in 2012 and released publicly in 2015, GraphQL provides a complete and understandable description of the data in an API.

Unlike REST architectures, which expose multiple endpoints returning fixed data structures, GraphQL typically operates via a single HTTP endpoint. Clients define the exact shape and fields of the response they require. This design eliminates common API inefficiencies:

GraphQL relies on a strongly typed schema definition. The schema defines types, relationships, queries (for read operations), and mutations (for write operations).

How JavaScript Clients Query Structured Data

JavaScript applications interact with a GraphQL API by sending HTTP POST requests with a payload containing a query string and optional variables. While standard tools like fetch or Axios can handle these requests, specialized GraphQL client libraries—such as Apollo Client, Relay, or URQL—streamline the workflow.

A typical query lifecycle in a JavaScript application involves the following steps:

  1. Defining the Query: Developers write declarative queries using the GraphQL syntax, often wrapped in a template literal tag (such as gql).

    import { gql } from '@apollo/client';

const GET_USER_PROFILE = gql`
  query GetUserProfile($userId: ID!) {
    user(id: $userId) {
      id
      name
      email
      posts {
        id
        title
      }
    }
  }
`;

  2. Executing the Request: The client library executes the request through React hooks (e.g., useQuery), Vue composables, or direct asynchronous function calls.

  3. Parsing the Response: The server validates the query against its schema, resolves the data, and returns a JSON response matching the structure of the request:

    {
  "data": {
    "user": {
      "id": "123",
      "name": "Jane Doe",
      "email": "jane@example.com",
      "posts": [
        { "id": "1", "title": "Understanding GraphQL" }
      ]
    }
  }
}

How JavaScript Clients Cache Structured Data

Because GraphQL queries return custom, deeply nested data structures from a single endpoint, standard HTTP-level caching (such as caching based on URL paths) is ineffective. To solve this, JavaScript clients implement normalized caching.

Normalized caching works through a deterministic process:

  1. Demultiplexing / Flattening Objects: When a query response arrives, the cache flattens the nested tree structure into individual records.
  2. Generating Unique Identifiers: The cache creates a global key for every object using its type name and unique identifier, typically in the format TypeName:id (e.g., User:123 or Post:1).
  3. Storing Normalized Entities: The client stores these records in a flat, lookup-table-style dictionary. Nested relationships are replaced with references (pointers) to the respective normalized keys.
  4. Reconstructing Results: When a component requests data, the client reconstructs the required tree structure by dereferencing the pointers from the flat cache.

Benefits of Client-Side Caching