How to Use the Cursor In GraphQL?

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The cursor in GraphQL is a string-based pagination technique used to navigate through large lists of data. It allows for efficient and constant-time pagination by using opaque strings as pointers to individual records.

To use the cursor in GraphQL, you need to follow these steps:

  1. Implement cursor-based pagination: Modify your GraphQL schema to include a cursor field, which represents the position of a record in the list. Typically, this field is of type String or a custom Cursor type defined in your schema.
  2. Update the resolver: Modify the resolver function for the paginated field to accept an optional cursor parameter. This parameter represents the position where the next page of results should start. You can use various algorithms and techniques to generate and parse cursor values.
  3. Perform pagination query: When querying for paginated data, you can provide the cursor value as an argument to the resolver function. The resolver then uses this cursor to determine the starting position for the next page of results.
  4. Return results with cursors: When returning paginated results, include the cursor for each record in the response. This cursor represents the position of the record in the list and is used to paginate to the next set of results.
  5. Fetch next page of results: To fetch the next page of results, pass the cursor of the last record in the current page as an argument to the paginated field. The resolver uses this cursor to determine the starting position for the next page of results.

By using cursors in GraphQL, you can efficiently paginate through large datasets without having to load all the data at once. Cursors provide a consistent and reliable way to traverse the data set in a predictable order, enabling efficient pagination for clients consuming GraphQL APIs.

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What are the best strategies for cursor-based pagination in GraphQL subscriptions?

When implementing cursor-based pagination in GraphQL subscriptions, consider the following strategies:

  1. Establish a unique cursor: Instead of relying on an arbitrary field for cursor-based pagination, create a unique identifier for each item being paginated. This ensures that subsequent requests can accurately identify the items to be fetched.
  2. Bidirectional pagination: Enable pagination in both forward and backward directions. By allowing users to fetch previous or next pages, you provide them with more flexibility.
  3. Use relay-style cursors: Follow the Relay cursor specification ( to generate opaque cursors that contain enough information to determine the current position and the direction of pagination.
  4. Implement cursor sanitization: To prevent potential security issues or inconsistencies, sanitize and validate cursors received from the client before processing them. Ensure that the cursors are associated with the appropriate data and within the expected boundaries.
  5. Include metadata and total count: Along with the paginated data, return metadata such as the total number of items and information on whether there are more pages available. This helps clients to display pagination controls and limit unnecessary requests.
  6. Handle subscription changes: When a subscription result alters the paginated data, make sure the cursor-based pagination remains intact. New items should be correctly placed based on their cursor values, and deleted items should not reappear in subsequent requests.
  7. Optimize caching and performance: Utilize existing caching mechanisms like client-side caching, server-side caching with tools like Redis, or implementing a dataloader pattern to avoid redundant fetching of previously requested data.
  8. Balance real-time updates and data freshness: Consider the trade-off between real-time updates and data freshness. Subscribing to all changes in real-time may provide immediate updates but can increase traffic and server load. Consider implementing strategies like debouncing, throttling, or batching updates to maintain a balance.

Remember, the best strategy depends on the specific use case and requirements. Adjust these strategies based on your application's complexity and performance needs.

How to implement infinite scrolling using the cursor in GraphQL?

In GraphQL, implementing infinite scrolling using the cursor involves a combination of cursors (which represent the current position in the data) and pagination.

Here's a step-by-step guide on how to implement infinite scrolling with cursors in GraphQL:

  1. Define a query that supports cursor-based pagination. This query should take in arguments for the number of items to fetch (first or last) and a cursor to specify the starting point.
query MyQuery($first: Int, $after: String) {
  myData(first: $first, after: $after) {
    pageInfo {
    edges {
      node {
        # fields to fetch

  1. In your GraphQL server, implement the resolver for the myData field. The resolver should make use of the first and after arguments to determine the starting point of the data to fetch. Also, limit the number of items returned according to the first or last argument.
  2. On the client-side, make an initial query with a specified first value to fetch a certain number of records.
  3. Once the initial data is fetched, extract the endCursor value from the pageInfo field. Store this value as the initial after cursor.
  4. When the user scrolls down, trigger another query and pass the stored endCursor value as the after argument.
  5. Use the received data to append new items to the existing list of records.
  6. If the hasNextPage value in the pageInfo field is true, repeat steps 4-6 to fetch more data as the user continues to scroll.

By using cursors and pagination in this way, you can implement infinite scrolling in GraphQL.

What is the difference between a cursor and an offset in GraphQL?

In GraphQL, both the cursor and offset are used for pagination purposes, but they differ in their approach and how they handle pagination.

  1. Offset: Offset-based pagination involves specifying the number of items to skip in the result set to retrieve the next set of data. It requires the client to keep track of the current offset and increment it for each subsequent request. For example, if you have retrieved 10 items in the initial request using an offset of 0, you would use an offset of 10 to retrieve the next 10 items.


  • It is straightforward to implement, as it only requires incrementing and using offsets.
  • The client has control over which page to retrieve.


  • It can be inefficient for large datasets, as each request must skip a fixed number of items, leading to performance issues and slow response times.
  • If new items are added or removed between requests, the client may encounter data inconsistency.
  1. Cursor: Cursor-based pagination, also known as keyset pagination, involves using a cursor (a unique identifier) to indicate the position from where the next set of data should be fetched. The cursor usually represents a specific item in the result set. For example, after retrieving a set of items, the last item's cursor can be used to fetch the next set.


  • It provides more efficient pagination for large datasets, as only the necessary data is fetched.
  • It can handle inserts and deletes more gracefully, as the position in the result set is determined by the cursor.


  • Clients need to keep track of the cursors and ensure they are used correctly.
  • It requires more complexity to implement, as the queries must be constructed with cursor-based logic.

Overall, cursor-based pagination is recommended for most scenarios due to its performance advantages and flexibility in handling data changes. However, offset-based pagination can still be useful for smaller datasets or certain use cases where simplicity is prioritized.

What are some common cursor-related performance optimizations in GraphQL?

There are several common cursor-related performance optimizations in GraphQL that can improve query performance and reduce the impact on server resources. Some of these optimizations include:

  1. Pagination with Cursors: Instead of using traditional page-based pagination (limit-offset), GraphQL can use cursor-based pagination. Cursors can represent an arbitrary position in a list of results, allowing clients to request specific "pages" of data while avoiding the overhead of skipping or offsetting results. It can be achieved by using an opaque cursor string or a unique identifier from the underlying data source.
  2. Indexing and Sorting: When using cursors, it is essential to create proper indexes on the database columns used for sorting or filtering. Indexing can significantly improve the retrieval speed of data when using cursors in GraphQL. Additionally, sorting on indexed fields can be faster and more efficient.
  3. Caching: Implementing caching mechanisms like the use of a distributed cache or a CDN can help reduce the need for repeated computations and database queries. Caching results based on cursor parameters can be particularly effective when combined with cursor-based pagination.
  4. Connection-Level Caching: By caching the results of individual connections in the GraphQL server, subsequent similar queries can benefit from the cached response. This can avoid redundant queries to the underlying data source, speeding up the GraphQL server's overall performance.
  5. Fetching Only Necessary Fields: In GraphQL, clients can specify precisely which fields they require from a particular query. By fetching only the necessary fields and avoiding excessive data fetching, unnecessary server load and data transfer can be minimized, resulting in improved performance.
  6. Query Complexity Analysis: Implementing query complexity analysis can help identify and limit the complexity of cursor-related queries. By setting limits or prioritizing simpler queries, the server can ensure that resource-intensive operations are properly controlled.
  7. Debouncing or Throttling Cursors: In scenarios where clients send multiple sequential requests with cursor parameters, it may be beneficial to implement debouncing or throttling mechanisms. These mechanisms can prevent excessive cursor-based queries from overwhelming the server, optimizing resource utilization.
  8. Batch Loading: When resolving cursor-based queries, batch loading techniques can be used to minimize the number of database queries or remote calls required. By grouping related queries and fetching data efficiently, overall query performance can be improved.

It's important to note that the exact optimizations to employ may depend on the specific GraphQL implementation, data source, and application requirements.

How to store and retrieve cursors in a GraphQL database?

In GraphQL, cursors are often used for pagination and implementing efficient cursor-based pagination can greatly improve the performance and user experience of your application. Here's how you can store and retrieve cursors in a GraphQL database:

  1. Define a field in your GraphQL schema to represent the cursor: This field will typically be of scalar type (e.g., String or ID) and will be used to identify a specific item in the queried list.
  2. When querying for a list of items: Along with the list of items, include the cursor value for each item. The cursor value can typically be derived from an existing field present in the queried item (such as a unique identifier or a timestamp).
  3. When storing the cursor value in your database: Ensure that the cursor value is associated with the queried item. You can store the cursor as an additional field in your database table/collection or encode and store it within an existing field.
  4. When retrieving the next set of results: Specify the "after" cursor value in the GraphQL query to get the subsequent items. Query the database using this cursor value to fetch the items that come after the specified cursor.
  5. Implement checks to validate the cursor: Ensure that the provided cursor is valid and corresponds to an existing item in your database. Return an appropriate error if the cursor is invalid or not found.
  6. To efficiently paginate large datasets, consider: Indexing the field(s) used for generating cursors to improve the performance of fetching items based on a cursor value. Limiting the maximum number of items that can be fetched in a single query to avoid excessively large result sets.

By following these steps, you can effectively store and retrieve cursors in a GraphQL database to enable efficient cursor-based pagination.

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