This animation explains why APIs break large datasets into pages instead of returning millions of records at once, reducing database, server, and network load. It walks through Offset Pagination using limit and offset, showing how it can cause missing or duplicate records when data changes, then contrasts this with Cursor Pagination, which continues from a known position for more reliable results. Useful for backend developers, API designers, and engineers building scalable data retrieval systems.
Narrated · 16:9 · Preview before teaching · automatic layout checks do not establish subject accuracy
What happens when an API needs to return millions of transactions? Returning everything in a single response can put unnecessary load on the database and server, consume memory and bandwidth, and create a slow experience for the client. This is where Pagination comes in. In this video, we’ll understand how pagination helps APIs return large datasets efficiently, and then compare the two common approaches: Offset Pagination and Cursor Pagination. We’ll cover: What is Pagination? Why APIs shouldn't return millions of records at once How pagination reduces database, server, and network load Page-based data retrieval Offset Pagination limit and offset Problems with Offset Pagination How changing data can cause missing or duplicate records Cursor Pagination How cursors work Why Cursor Pagination is more reliable for dynamic datasets Offset vs Cursor Pagination When to use Offset Pagination When to use Cursor Pagination Pagination for large and frequently changing datasets The simple idea: Offset Pagination skips a fixed number of records. Cursor Pagination continues from a known position. Offset pagination is simple and useful for relatively stable datasets, while cursor pagination is often a better choice for large, frequently changing datasets where consistency matters. Audience: Professionals