Introduction to MongoDB Data Modeling

1. What is Data Modeling?

Data modeling is the process of creating a data model for the data to be stored in a database. In MongoDB, it involves designing the structure of your documents, collections, and overall database architecture.

2. Key Concepts

2.1 Documents

Documents are the basic unit of data in MongoDB, stored in a format called BSON (Binary JSON).

2.2 Collections

A collection is a grouping of MongoDB documents, similar to a table in relational databases.

2.3 Databases

A database is a container for collections. Each MongoDB instance can hold multiple databases.

3. Data Modeling Techniques

MongoDB supports two primary data modeling techniques: embedding and referencing.

3.1 Embedding

Embedding involves storing related data in a single document. This is useful for one-to-few relationships.

Example:


{
    "_id": 1,
    "name": "John Doe",
    "address": {
        "street": "123 Main St",
        "city": "Anytown"
    }
}

3.2 Referencing

Referencing involves using ObjectIDs to link documents across collections. This is useful for one-to-many relationships.

Example:


{
    "_id": 1,
    "name": "John Doe",
    "order_id": ObjectId("603d8d3e0e1a5e4f0c8c4a4a")
}

4. Best Practices

Understand your data access patterns before modeling.
Use embedding for related data that is frequently queried together.
Use referencing for data that may change independently.
Keep documents under 16MB to ensure performance.

5. FAQs

What is the maximum document size in MongoDB?

The maximum document size is 16MB.

When should I use embedding vs referencing?

Use embedding for data that is queried together and referencing for data that changes independently.