Which pagination approach is most scalable for large address datasets when supplying filtering and sorting?

Which pagination approach is most scalable for large address datasets when supplying filtering and sorting?

• A. Limit/Offset pagination is simplest but less scalable at scale.
• B. Page-based pagination with page numbers is best for scalability.
• C. Cursor-based pagination with a stable sort key is commonly adopted for large datasets.
• D. Cursor-based pagination using a forward-only token (server-issued cursor) provides scalability and consistent results.

Answer: (D)

The main idea is to paginate in a way that keeps the query fast and the results predictable as the dataset grows and changes with filtering and sorting. Limiting with an offset forces the database to skip over many rows to reach the desired page, which gets slow at scale and can yield inconsistent results if new rows are inserted or deleted between requests. Using page numbers shares these drawbacks and also requires extra work to count total pages, which becomes costly on large datasets. A cursor-based approach that uses a stable sort key improves performance by turning pagination into a range query on an indexed column, avoiding the heavy skipping of offsets. When that cursor is a forward-only token issued by the server, the client simply passes it along to fetch the next page, ensuring scalability and consistent ordering even as data changes. This combination—forward-only server-issued cursors with a stable sort—is how systems reliably handle large, filtered, and sorted datasets at scale.