To efficiently fetch and display millions of records from a database, you should never load all records at once. Instead, follow these optimized strategies:
✅ 1. Pagination (LIMIT & OFFSET)
- Fetch small chunks (e.g., 50 or 100 records) per request.
-
Backend:
SELECT * FROM records LIMIT 100 OFFSET 200; - Frontend: Use pagination UI to fetch page-wise data.
✅ 2. Cursor-based Pagination (Keyset Pagination)
- More efficient than OFFSET for large datasets.
-
Instead of skipping rows, use a reference key:
SELECT * FROM records WHERE id > last_seen_id LIMIT 100;
✅ 3. Infinite Scrolling / Lazy Loading
- Load more records only when the user scrolls to the bottom.
- Improves UX for large lists (e.g., Facebook feed).
✅ 4. Indexing
- Ensure columns used for filtering/sorting (like
id,created_at) are indexed. - Indexes make queries faster, especially with WHERE or ORDER BY.
✅ 5. Data Caching
- Use Redis or in-memory cache for frequently accessed data.
- Reduces database load.
✅ 6. Server-side Filtering, Sorting, and Searching
- Only send filtered/sorted data to frontend.
- Avoid fetching entire datasets and filtering on the frontend.
✅ 7. Backend Best Practices
- Use streaming (e.g.,
.stream()in Node.js or cursors in MongoDB). - Avoid
SELECT *— fetch only required fields.
✅ 8. Frontend Virtualization
- Use libraries like
react-windoworreact-virtualizedto render only visible rows in the DOM. - Great for performance in huge tables/lists.
🧠 Summary:
Paginate, Index, Cache, Stream, and Virtualize — these are the keys to handling millions of records efficiently.
