Why should you care?

Feeds must feel instant. Modeling posts and fan-out/fan-in choices decides whether you survive a viral spike.

See it live — copy this example

Open mongosh or MongoDB Compass, select database nosqlverse, then run the example. Change one field and run again.

db.users.insertOne({ _id: "u1", username: "neha", followers: 120 })
db.posts.insertOne({
  authorId: "u1",
  text: "Loving MongoDB aggregations!",
  tags: ["mongodb", "nosqlverse"],
  likeCount: 0,
  createdAt: new Date()
})
db.follows.insertOne({ followerId: "u2", followeeId: "u1", at: new Date() })
db.posts.find({ authorId: { $in: ["u1", "u3"] } }).sort({ createdAt: -1 }).limit(20)
db.posts.createIndex({ authorId: 1, createdAt: -1 })

Run Example »

Edit the code below and click Run to see the result in Toolliyo’s live editor.

What happened?

• posts reference authorId.
• follows links users.
• A simple home feed loads posts from followee ids sorted by time.
• Index authorId+createdAt supports that path.

Practice next

1. Create users, posts, follows collections.
2. Insert sample graph data.
3. Query a feed with $in of followee ids.
4. Add comments as a separate collection referencing postId.
5. Use $lookup to join author usernames for a feed API.

Remember

Posts + follows are core collections. Index author timelines. Plan viral outliers early.

NoSQLVerse community feed

Learners follow mentors and see their Mongo tips newest first.

Outcome: Feed API stays simple and indexed.