str): self.id = id self.content = content

Mock database interaction for demonstration purposes

In a real application, this would be a database query.

_mock_db = [FeedItem(i, f”Item {i}”) for i in range(1, 1000001)]

@router.get(“/api/v1/feed”, response_model=dict) def get_paginated_feed( # For the initial request, last_id can be 0 or None last_id: int = Query(0, description=”The ID of the last item seen in the previous batch.”), page_size: int = Query(50, ge=1, le=100) ) -> dict: “”” Retrieves a paginated list of feed items using cursor-based pagination. “”” # The critical SQL pattern: WHERE id > last_id ORDER BY id ASC LIMIT page_size # This use the index on ‘id’ for efficient lookup.

# Simulate database query:
# In a real application, this would be an ORM query like:
# results = session.query(FeedItem).filter(FeedItem.id > last_id).order_by(FeedItem.id.asc()).limit(page_size).all()

filtered_items = [item for item in _mock_db if item.id > last_id]
sorted_items = sorted(filtered_items, key=lambda x: x.id) # Ensure order for consistent pagination
results = sorted_items[:page_size]

# Determine the cursor for the next request
next_cursor: Optional[int] = results[-1].id if results else None

return {
    "data": [{"id": item.id, "content": item.content} for item in results],
    "next_cursor": next_cursor
}

```

So, who’s making money here? The database vendors who sell you performant indexing, sure. But more importantly, the companies that don’t want their services grinding to a halt under the weight of their own success. And frankly, developers who want to sleep at night without debugging infinite loading spinners.

Is this a paradigm shift? No. It’s a course correction. It’s acknowledging that a popular, easy-to-teach technique has fundamental scaling limitations that we can no longer afford to ignore, especially with AI and ever-growing data lakes. The transition to cursor pagination isn’t a trendy buzzword; it’s the pragmatic engineering required to keep your applications functional and your users (and your wallet) happy. Get ahead of it now, before your OFFSET queries become the digital equivalent of dial-up internet in a 5G world.

Why Does Cursor Pagination Beat the Old Way?

The fundamental difference is how the database finds the data. OFFSET requires a full scan and discard of preceding rows, meaning performance degrades linearly with the offset amount. Cursor pagination, on the other hand, uses a specific identifier (the cursor) to perform an indexed lookup, which is vastly more efficient and scales logarithmically. This means consistent, fast retrieval no matter how deep into your dataset you go.

Who is This Actually For?

This isn’t just for the giants. Anyone dealing with more than a few thousand records, especially if those records are frequently added or modified, will feel the pain of OFFSET pagination. This includes e-commerce sites with large product catalogs, social platforms with active feeds, any application displaying historical data, and especially any system that relies on automated data retrieval or scraping. Basically, if your data isn’t static and your dataset is growing, you need to care.

**

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Frequently Asked Questions**

What does cursor pagination actually do? Cursor pagination provides a more efficient way to retrieve large datasets in chunks. Instead of relying on numerical page numbers (like OFFSET), it uses a pointer or