Designing Efficient MongoDB Schemas
MongoDB's flexible document model allows for powerful data modeling, but following best practices ensures optimal performance and maintainability.
Understanding Document Structure
MongoDB stores data in BSON documents. Design your documents to match your application's data access patterns.
Embedding vs Referencing
Choose between embedding and referencing based on:
- Data size and growth
- Query patterns
- Update frequency
- Data consistency requirements
Schema Design Patterns
One-to-One Relationships
Embed related data in the same document when it's always accessed together.
One-to-Many Relationships
Embed when the "many" side has few items, reference when it can grow large.
Many-to-Many Relationships
Use arrays of references or a separate collection for the relationship.
Indexing Strategies
Create indexes based on your query patterns:
- Single field indexes
- Compound indexes
- Text indexes for search
- Geospatial indexes for location data
Performance Considerations
- Avoid deeply nested documents
- Keep document size reasonable (< 16MB)
- Design for your read/write patterns
- Use aggregation pipelines for complex queries
