Embedding documents in MongoDB is a common approach to improving performance, especially when dealing with one-to-few or one-to-many relationships. Instead of using references (i.e., storing related data in separate collections and linking them with ObjectIDs), embedding keeps all relevant data together within a single document. This reduces the need for joins and extra queries, improving read performance.
Best Practices for Embedding Documents
Use embedding for related data that is frequently accessed together
Example: A blog post and its comments are often fetched together.
{ "_id": ObjectId("abc123"), "title": "MongoDB Performance Tips", "content": "Learn how to embed documents for better performance.", "author": "Nidhi", "comments": [ { "user": "John Doe", "comment": "Great article!", "timestamp": "2025-02-20T10:00:00Z" }, { "user": "Jane Smith", "comment": "Very helpful!", "timestamp": "2025-02-20T11:00:00Z" } ]}
Benefit: Fetching a blog post also retrieves its comments in a single query.
Avoid embedding large or frequently changing subdocuments
If a subdocument grows indefinitely (e.g., chat messages in a group), it’s better to reference them separately.
Example: Instead of embedding all messages in a chat room, store them in a separate collection.
Keep document sizes under 16MB
MongoDB has a 16MB document limit, so deeply nested or large arrays can cause performance issues.
Optimize for read-heavy operations
If your application frequently reads data but updates less often, embedding can be a great option.
Use array indexing when necessary
If searching inside an embedded array is common, use an index on array fields for faster lookups.
Example: Creating an index on the comments.user field.
db.blogPosts.createIndex({ "comments.user": 1 });
