Keyset Pagination With Range Queries
Learners will build cursor-based pagination using a range filter on _id or a timestamp field, achieving consistent O(log n) page performance.
Keyset Pagination With Range Queries is a free MongoDB Academy lesson on CoddyKit — lesson 3 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the MongoDB Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
What Is Keyset Pagination?
Keyset pagination—also called cursor pagination—avoids skip() entirely by using a range query on the sort key. Instead of telling MongoDB 'jump over the first N documents', you tell it 'give me documents where the sort key is greater than the last value I saw'. This is always O(log n) because it uses an index range scan, regardless of how far into the result set you are.
The Core Concept: A Range Filter as a Cursor
After fetching the first page, you remember the sort key value of the last document returned. For the next page, you filter documents where the sort key is strictly greater than (or less than, for descending) that remembered value. This filter combined with an index gives MongoDB an exact starting point—no skipping needed.
// First page — no cursor needed
const page1 = await db.collection('posts')
.find({ isPublished: true })
.sort({ createdAt: -1, _id: -1 })
.limit(20)
.toArray();
// Remember the last document's sort keys
const lastCreatedAt = page1[page1.length - 1].createdAt;
const lastId = page1[page1.length - 1]._id;Fetching the Next Page With a Range Query
Use the remembered sort key values in a $lt (or $gt for ascending) condition for the next page query. No skip() is needed—the range condition navigates the index directly to the right starting position. MongoDB fetches limit documents starting from that point.
// Next page: posts older than the last one seen
// Descending by createdAt means 'older' = $lt
const page2 = await db.collection('posts')
.find({
isPublished: true,
$or: [
{ createdAt: { $lt: lastCreatedAt } },
{ createdAt: lastCreatedAt, _id: { $lt: lastId } } // tiebreaker
]
})
.sort({ createdAt: -1, _id: -1 })
.limit(20)
.toArray();Why Include _id as a Tiebreaker?
Multiple documents may have the same createdAt timestamp (e.g., many items inserted in the same second). Without a tiebreaker, the range boundary is ambiguous and you might skip or duplicate documents at the boundary. Adding _id as a secondary sort field and including it in the range condition makes the cursor uniquely deterministic—no document can have the same (createdAt, _id) pair.
// Compound index to support the keyset query
db.posts.createIndex({ createdAt: -1, _id: -1 });
// This index covers both the sort and the range filterKeyset Pagination on _id Alone
If you sort purely by _id (default insertion order), keyset pagination is the simplest possible form. _id is always unique and already indexed. Each page returns documents where _id is greater than the last seen value. This works perfectly for feed-style queries where insertion order is the natural sort.
// First page
const page1 = await db.collection('events')
.find({})
.sort({ _id: 1 })
.limit(50)
.toArray();
const lastId = page1[page1.length - 1]._id;
// Next page — range filter on _id
const page2 = await db.collection('events')
.find({ _id: { $gt: lastId } })
.sort({ _id: 1 })
.limit(50)
.toArray();Encoding the Cursor for API Responses
API clients should not need to know the internal cursor format. Encode the cursor as a Base64 or JWT string that the server can decode on the next request. This hides the implementation detail (whether you use createdAt, _id, or a composite key) from clients and lets you change the cursor format without breaking the API contract.
// Encode cursor
function encodeCursor(doc) {
return Buffer.from(JSON.stringify({ createdAt: doc.createdAt, _id: doc._id })).toString('base64');
}
// Decode cursor
function decodeCursor(token) {
return JSON.parse(Buffer.from(token, 'base64').toString('utf-8'));
}
// API response
const nextCursor = page.length === PAGE_SIZE ? encodeCursor(page[page.length - 1]) : null;
res.json({ data: page, nextCursor });Keyset Pagination in an Express Handler
A complete keyset pagination handler decodes the incoming cursor (if provided), builds the range filter, runs the query, encodes the next cursor, and returns the response. If there is no next cursor to return (the page is smaller than the page size), the client knows it has reached the last page.
async function listPosts(req, res) {
const limit = 20;
let filter = { isPublished: true };
if (req.query.cursor) {
const { createdAt, _id } = decodeCursor(req.query.cursor);
filter['$or'] = [
{ createdAt: { $lt: new Date(createdAt) } },
{ createdAt: new Date(createdAt), _id: { $lt: _id } }
];
}
const posts = await Post.find(filter).sort({ createdAt: -1, _id: -1 }).limit(limit).lean();
const nextCursor = posts.length === limit ? encodeCursor(posts[posts.length - 1]) : null;
res.json({ data: posts, nextCursor });
}Keyset vs Offset: Performance Comparison
Imagine a collection with 1,000,000 posts. Offset pagination to page 1000 (20 items/page) executes skip(19980)—MongoDB walks 19,980 index entries. Keyset pagination uses a range filter: { createdAt: { $lt: someDate } }—MongoDB does a binary search on the index to find the starting point and scans exactly 20 entries. The difference at scale: milliseconds vs seconds.
Limitations of Keyset Pagination
Keyset pagination has two notable limitations: (1) you cannot jump to an arbitrary page number—you can only go forward or backward one page at a time; (2) the sort field must be part of the cursor, so sorting by non-unique, non-indexed fields requires careful tiebreaker selection. These trade-offs make keyset pagination unsuitable for applications that require page-number navigation, but it is the correct choice for infinite scroll and API cursor patterns.
Bidirectional Keyset Pagination
To support both 'next page' and 'previous page' navigation, store both the cursor for the first document and the cursor for the last document on each page. Use $gt with the first document's cursor to go backward. Reverse the sort direction for the backward query, then re-reverse the results before returning them.
// Previous page — documents newer than the first item on the current page
const prevPage = await db.collection('posts')
.find({
isPublished: true,
createdAt: { $gt: firstDocCreatedAt }
})
.sort({ createdAt: 1, _id: 1 }) // reverse sort for previous page
.limit(20)
.toArray();
prevPage.reverse(); // flip back to descending display orderIndex Design for Keyset Pagination
The compound index for a keyset pagination query should include: filter fields first (equality conditions), then the sort fields. For example, if you filter by isPublished and sort by createdAt DESC, _id DESC, the ideal index is { isPublished: 1, createdAt: -1, _id: -1 }. This index covers the equality filter and the range sort without any in-memory operations.
// Ideal covering index for keyset pagination on posts
db.posts.createIndex({ isPublished: 1, createdAt: -1, _id: -1 });
// Verify with explain — expect IXSCAN, no SORT stage
db.posts.find({ isPublished: true, createdAt: { $lt: new Date() } })
.sort({ createdAt: -1, _id: -1 })
.limit(20)
.explain('executionStats');Quick Check
Test your understanding of MongoDB & NoSQL Databases concepts from this lesson.
Lesson Recap
In this lesson you learned: keyset pagination uses a range filter on the last seen sort key instead of skip(), this achieves O(log n) performance regardless of page depth, and including _id as a tiebreaker prevents duplicate or missing documents at sort boundaries. Next up we practice combining sort, skip, limit, and projections into a complete query chain.
Frequently asked questions
Is the “Keyset Pagination With Range Queries” lesson free?
Yes — the full text of “Keyset Pagination With Range Queries” is free to read here on the web, and the MongoDB Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the MongoDB Academy course, upgrade to CoddyKit PRO.
What will I learn in “Keyset Pagination With Range Queries”?
Learners will build cursor-based pagination using a range filter on _id or a timestamp field, achieving consistent O(log n) page performance. You practise MongoDB Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start MongoDB Academy?
No prior experience is required. MongoDB Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 3 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Keyset Pagination With Range Queries” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this MongoDB Academy lesson?
Yes. Every MongoDB Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Sorting With sort() and Multiple Keys
- Skip and Limit: Offset Pagination
- Keyset Pagination With Range Queries
- Combining Sort, Skip, Limit, and Projections