Embedded Data Versus References

Use Cases

Use embedded data models in the following scenarios:

• You have "contains" relationships between entities. For example, a contacts document that contains an address. See Model One-to-One Relationships with Embedded Documents.

• You have one-to-many relationships between entities. In these relationships, the "many" or child documents are viewed in the context of the "one" or parent documents. See Model One-to-Many Relationships with Embedded Documents.

Embedding provides the following benefits:

• Better performance for read operations

• The ability to retrieve related data in a single database operation

• The ability to to update related data in a single atomic write operation

Query Embedded Data

To query data within embedded documents, use dot notation. For examples of querying data in arrays and embedded documents, see:

• Query an Array

• Query on Embedded/Nested Documents

Use Cases

Use references to link related data in the following scenarios:

• Embedding would result in duplication of data but would not provide sufficient read performance advantages to outweigh the implications of the duplication. For example, when the embedded data frequently changes.

• You need to represent complex many-to-many relationships or large hierarchical data sets.

• The related entity is frequently queried on its own. For example, if you have employee and department data, you may consider embedding department information in the employee documents. However, if you often query for a list of departments, your application will perform best with a separate department collection that is linked to the employee collection with a reference.

Query Normalized Data Models

To query normalized data in multiple collections, MongoDB provides the following aggregation stages:

• $lookup

• $graphLookup

For an example of normalized data models, see Model One-to-Many Relationships with Document References.

For examples of various tree models, see Model Tree Structures.