Imagine your application has 500,000 users.
Someone opens:
/users
Should your API return all 500,000 records?
Probably not.
Large Responses Create Multiple Problems
Returning huge datasets can increase:
Database work Memory usage API response time Network traffic Browser memory usage
Even if the query succeeds, the user doesn't need half a million records on one page.
Pagination Solves the Problem
Instead of:
GET /users
returning everything, use something like:
GET /users?page=1&limit=50
Now the application only retrieves a manageable number of records.
Cursor Pagination Can Help Too
For very large datasets, cursor-based pagination can be more efficient than repeatedly calculating offsets.
Instead of saying:
Give me page 1000.
you can say:
Give me the next 50 records after this item.
The exact approach depends on your database and application.
Don't Just Paginate the UI
A common mistake is loading everything from the database and only showing 20 items in the browser.
That's not real pagination.
The database query itself should limit the amount of data returned.
Protect Your API
Pagination also gives you a useful safety boundary.
An endpoint shouldn't allow someone to request:
limit=10000000
without restrictions.
Set reasonable limits.
A Simple Rule
If a table can grow significantly, design pagination from the beginning.
It is much easier than rebuilding an API after it becomes slow.
Hostwares' database guidance also recommends limiting result sets and using pagination for large tables.
Don't make the database send you data the user never asked to see.