Apollo Client is a client-side GraphQL library that helps React applications execute operations and manage GraphQL data.

A GraphQL client is responsible for more than sending HTTP requests. Apollo Client can provide:

• Query execution
• Mutation execution
• Request state management
• Normalized caching
• Cache updates
• Optimistic UI
• Polling
• Refetching
• Pagination helpers
• Error handling

A useful mental model is:

React Component
      ↓
Apollo Client
      ↓
Cache ────────┐
      ↓       │
GraphQL Link │
      ↓       │
GraphQL API  │
      ↓       │
Response ────┘

Apollo Client can first satisfy a query from its cache depending on the configured fetch policy and then communicate with the server when required.

This is one of the major differences between using a raw fetch() call and using a full GraphQL client library.

A React application typically creates an Apollo Client instance and provides it to the component tree.

Conceptually:

const client = new ApolloClient({
  uri: "/graphql",
  cache: new InMemoryCache()
});

The application then provides the client through Apollo's React integration.

<ApolloProvider client={client}>
  <App />
</ApolloProvider>

Components below the provider can use GraphQL hooks such as useQuery and useMutation.

The InMemoryCache is a normalized cache. It can store entities and references rather than simply caching entire query responses as opaque blobs.

In production applications, the Apollo Client setup often also includes an authentication link, error handling, retry behavior, upload support, tracing headers, or other transport concerns.

Keep transport configuration centralized instead of recreating clients inside individual React components.

Apollo Client's useQuery hook connects a React component to a GraphQL query.

For example:

const GET_USER = gql`
  query GetUser($id: ID!) {
    user(id: $id) {
      id
      name
      email
    }
  }
`;

A component can use it:

const { data, loading, error } = useQuery(GET_USER, {
  variables: { id }
});

The component should account for at least three broad states:

Loading
   ↓
Success ─────→ Render data
   ↓
Error ───────→ Render error state

A production component should not assume data exists immediately.

For example:

if (loading) return <Spinner />;
if (error) return <ErrorMessage />;
if (!data?.user) return <NotFound />;

return <UserProfile user={data.user} />;

The exact UI depends on the application, but the important concept is that server state is asynchronous and can change independently of the component lifecycle.

Apollo Client provides fetch policies that determine how a query interacts with the cache and network.

Common policies include:

cache-first

Use cached data when available. Otherwise request from the network.

network-only

Always request fresh data from the network and update the cache with the result.

cache-only

Read from the cache without making a network request.

no-cache

Request from the network without storing the result in the cache in the normal way.

cache-and-network

Return cached data when available while also requesting fresh network data.

The correct policy depends on the data.

For relatively stable reference data, cache-first can reduce unnecessary requests.

For rapidly changing data such as a live operational dashboard, network-only or cache-and-network may be more appropriate.

Do not choose network-only everywhere simply because freshness sounds safer. Doing so can throw away many of the benefits of client-side caching.

Conversely, do not use cache-first for data where stale information can create serious business problems without considering how and when the cache is invalidated.

Apollo Client's mutation APIs allow React components to trigger GraphQL mutations.

For example:

const CREATE_USER = gql`
  mutation CreateUser($input: CreateUserInput!) {
    createUser(input: $input) {
      id
      name
    }
  }
`;

The component can call:

const [createUser, { loading, error }] = useMutation(CREATE_USER);

Then:

await createUser({
  variables: {
    input: {
      name,
      email
    }
  }
});

After a mutation, the client cache may need to be updated.

Suppose the application has:

query Users {
  users {
    id
    name
  }
}

Creating a user does not necessarily mean Apollo can infer how your specific UI should update every query. Depending on the schema and cache configuration, you may need to use cache updates, refetching, or mutation result normalization.

A good client architecture treats mutation completion and cache consistency as explicit concerns.