Document Modeling Techniques in Multi-Model Databases

2.1 What is Document Modeling?

Document modeling refers to the process of designing the schema and structure of documents in databases where data is stored in a document format (e.g., JSON, XML).

2.2 Multi-Model Database

A multi-model database supports multiple data models (e.g., document, graph, key-value) under a unified architecture, allowing for greater flexibility in data management.

3.1 Schema Design

When designing document schemas, consider the following:

• Flat vs. Nested Structures
• Data Redundancy vs. Normalization
• Document Size Limitations

3.2 Example Document Model

Here’s an example of a JSON document for a user profile:

{
    "userId": "12345",
    "name": "John Doe",
    "email": "john.doe@example.com",
    "address": {
        "street": "123 Main St",
        "city": "Anytown",
        "state": "CA",
        "zip": "12345"
    },
    "hobbies": ["reading", "traveling", "swimming"]
}

3.3 Indexing Strategies

Utilize indexing to improve query performance:

• Single Field Indexing
• Compound Indexing
• Geospatial Indexing

4.1 Design for Query Patterns

Model documents based on the expected query patterns to optimize performance.

4.2 Limit Document Size

Keep documents within size limits (e.g., 16MB for MongoDB) to prevent performance issues.

4.3 Use Embedded Arrays Wisely

Embedding arrays can reduce the number of database reads but may lead to document bloat if not managed carefully.