MongoDB Database

3.

The MongoDB Data Model

3.1.

Fundamental Concepts

3.1.1.

3.1.1.1.

Database Creation and Deletion

3.1.1.2.

Database Naming Conventions

3.1.1.3.

Database-Level Operations

3.1.1.4.

Storage Engine Considerations

3.1.2.

3.1.2.1.

Collection Creation and Deletion

3.1.2.2.

Collection Naming Conventions

3.1.2.3.

Capped Collections

3.1.2.4.

Collection-Level Operations

3.1.2.5.

Collection Options and Properties

3.1.3.

3.1.3.1.

Document Structure and Format

3.1.3.2.

Document Size Limitations

3.1.3.3.

Document Identifiers (_id)

3.1.3.3.1.

ObjectId Generation

3.1.3.3.2.

Custom _id Values

3.1.3.3.3.

_id Uniqueness Requirements

3.1.3.4.

Document Validation Rules

3.2.

Document Structure

3.2.1.

Fields and Values

3.2.1.1.

Supported Data Types

3.2.1.1.1.

Primitive Types

3.2.1.1.2.

3.2.1.1.3.

3.2.1.2.

Field Naming Conventions

3.2.1.3.

Nested Fields and Subdocuments

3.2.1.4.

Array Fields and Elements

3.2.2.

Dot Notation for Embedded Documents and Arrays

3.2.2.1.

Accessing Nested Fields

3.2.2.2.

Querying Nested Data

3.2.2.3.

Array Element Access

3.2.2.4.

Positional Operators

3.3.

Schema Design Principles

3.3.1.

Dynamic and Flexible Schemas

3.3.1.1.

Advantages of Schema Flexibility

3.3.1.2.

Trade-Offs and Considerations

3.3.1.3.

Schema Evolution Strategies

3.3.2.

Schema Validation Options

3.3.2.1.

JSON Schema Validation

3.3.2.2.

Validation Rules and Actions

3.3.2.3.

Validation Performance Impact

3.3.3.

Data Modeling Patterns

3.3.3.1.

Embedded Document Pattern

3.3.3.1.1.

When to Embed Documents

3.3.3.1.2.

Embedding Limitations

3.3.3.1.3.

Pros and Cons Analysis

3.3.3.2.

Referenced Document Pattern

3.3.3.2.1.

When to Use References

3.3.3.2.2.

Reference Implementation Strategies

3.3.3.2.3.

Pros and Cons Analysis

3.3.3.3.

Hybrid Approaches

3.3.3.3.1.

Combining Embedding and Referencing

3.3.3.3.2.

Pattern Selection Criteria

3.4.

Modeling Relationships

3.4.1.

One-to-One Relationships

3.4.1.1.

Embedding Strategy

3.4.1.2.

Referencing Strategy

3.4.1.3.

Decision Criteria

3.4.2.

One-to-Many Relationships

3.4.2.1.

Embedding Arrays

3.4.2.2.

Array Size Considerations

3.4.2.3.

Referencing Collections

3.4.2.4.

Parent vs Child References

3.4.3.

Many-to-Many Relationships

3.4.3.1.

Linking Collections with Arrays

3.4.3.2.

Junction Collection Pattern

3.4.3.3.

Bidirectional References

3.4.3.4.

Query Optimization Strategies

3.5.

Advanced Schema Design Considerations

3.5.1.

Denormalization Strategies

3.5.2.

Data Duplication Trade-offs

3.5.3.

Query Pattern Analysis

3.5.4.

Performance Optimization

3.5.5.

Storage Efficiency

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4. CRUD Operations: Manipulating Data