Domain-Driven Database Design​

Vibra's database architecture follows domain-driven design principles, organizing collections into logical domains that reflect the business capabilities of the application:

• User Management: Handling authentication, authorization, and user profiles
• Activities and Learning: Managing educational content and user interactions
• Notifications: Supporting real-time user communication
• Permissions and Access Control: Implementing fine-grained security
• Organizations: Managing institutional hierarchies
• System Configuration: Controlling application behavior
• Audit and Reporting: Tracking system usage and generating insights

Key Collections and Relationships​

Let's explore some of the most important collections in our database and how they relate to each other:

Activities Domain​

The Activities collection is central to Vibra's educational functionality:

// Example Activity document
{
  "_id": ObjectId("60d21b4667d0d8992e610c85"),
  "id": "act-emotional-awareness-1",
  "emotions": "joy,surprise",
  "title": "Emotional Awareness Exercise",
  "resources": [
    {
      "type": "video",
      "url": "https://resources.vibra.co/videos/emotional-awareness.mp4",
      "duration": 180,
      "metadata": {
        "author": "Dr. Emma Rodriguez",
        "language": "es"
      }
    }
  ],
  "questions": [
    {
      "id": "q1",
      "questionText": "How did you feel after watching the video?",
      "type": "multiple-choice",
      "options": ["Happy", "Confused", "Inspired", "Neutral"],
      "correctAnswer": null,
      "points": 5
    }
  ],
  "difficulty": 2,
  "isActive": true,
  "schedule": {
    "date": ISODate("2025-12-06T00:00:00Z"),
    "weekNumber": 24,
    "year": 2025
  },
  "createdAt": ISODate("2025-12-06T14:30:00Z")
}

Activities are linked to Emotions, which categorize the emotional learning objectives:

// Example Emotion document
{
  "_id": ObjectId("60d21b4667d0d8992e610c86"),
  "id": "joy",
  "name": "Joy",
  "orientationNote": "Focus on positive experiences and gratitude",
  "description": "A feeling of great pleasure and happiness",
  "icono": "joy-icon.svg",
  "percentNote": 85
}

When users complete activities, their responses are stored in the UserResponses collection:

// Example UserResponse document
{
  "_id": ObjectId("60d21b4667d0d8992e610c87"),
  "user": "user123",
  "activity": "act-emotional-awareness-1",
  "responses": [
    {
      "questionId": "q1",
      "answer": "Inspired",
      "isCorrect": null,
      "responseTime": 12
    }
  ],
  "score": 5,
  "startTime": ISODate("2025-12-06T10:15:00Z"),
  "endTime": ISODate("2025-12-06T10:18:30Z"),
  "timeSpent": 210,
  "createdAt": ISODate("2025-12-06T10:18:30Z"),
  "updatedAt": ISODate("2025-12-06T10:18:30Z")
}

User Management Domain​

The Users collection stores comprehensive information about system users:

// Example User document
{
  "_id": ObjectId("60d21b4667d0d8992e610c88"),
  "name": "Maria Garcia",
  "documentType": ObjectId("60d21b4667d0d8992e610c89"),
  "documentNumber": "1098765432",
  "email": "maria.garcia@example.com",
  "username": "maria.garcia",
  "password": "$2a$10$hKDVYxLefVHV/vtuPhWD3OigtRyOykRLDdUAp80Z1crSoS1lFqaFS",
  "role": ObjectId("60d21b4667d0d8992e610c8a"),
  "company": ObjectId("60d21b4667d0d8992e610c8b"),
  "isActive": true,
  "createdAt": ISODate("2025-12-06T08:30:00Z")
}

Smart Database Design Patterns​

Our MongoDB implementation leverages several design patterns that enhance maintainability and performance:

1. Embedded Documents for Related Data​

We use embedded documents for closely related data that is always accessed together. For example, Activity documents embed Resources and Questions, optimizing read performance by reducing the need for joins.

2. References for Shared Data​

For data that is shared across multiple documents (like Users referenced by UserResponses), we use references to maintain data integrity and avoid duplication.

3. Soft Deletion Pattern​

Instead of permanently removing data, most collections implement soft deletion with deleted and deletedAt fields, preserving data for auditing while removing it from active use.

4. Comprehensive Audit Trails​

Most collections include creation and modification timestamps and user references, enabling detailed tracking of data changes over time.

Visualization of Key Relationships​

The diagram below illustrates the core relationships in our database:

graph TD
    Users --> Roles
    Users --> Companies
    Activities --> Emotions
    UserResponses --> Users
    UserResponses --> Activities
    Notifications --> NotificationTypes
    Permissions --> PermissionCategories
    UserPermissions --> Users
    UserPermissions --> Permissions

Performance Considerations​

To ensure optimal performance, we've implemented several strategies:

1. Strategic Indexing: We've created indexes on frequently queried fields to speed up searches
2. Data Denormalization: Where appropriate, we denormalize data to reduce the need for complex joins
3. Pagination: For large collections, we implement pagination to limit result sizes
4. Compound Indexes: For queries that filter on multiple fields, we use compound indexes

Conclusion​

Vibra's MongoDB architecture demonstrates how a well-designed database schema can support complex application requirements while maintaining flexibility and performance. By organizing collections into logical domains and implementing smart design patterns, we've created a data foundation that can evolve with the application's needs.

In future posts, we'll explore how our front-end components interact with this database structure and how we've implemented real-time features using MongoDB change streams.

🚀 Step-by-Step Guide: Migrating MongoDB from Local to Atlas

One of the most repetitive processes is migrating relational and non-relational databases from our on-premises environment to a cloud environment. This short post explains how to configure Atlas, create a backup, and restore a database in a basic migration process.

1️⃣ Prepare MongoDB Atlas​

✅ Create a Cluster: If you haven't already, head over to MongoDB Atlas and set up a free cluster (M0). Follow this guide for detailed instructions. ✅ User Configuration: Set up a user with read/write permissions (e.g., migrator). ✅ Network Access: Add your current IP (or use 0.0.0.0/0 temporarily) in Network Access.

Get the Atlas Connection String:

✅ Navigate to your cluster in https://cloud.mongodb.com/ and click "Connect".

✅ Choose "Connect your application".

✅ Copy the Connection String (e.g., mongodb+srv://user:password@clusterxxx.mongodb.net/).

MongoDB on MongoDB Atlas (Free)

📌 MongoDB Atlas

✅ Free to start: 512 MB of storage (enough for development).

✅ Managed: You don't need to install MongoDB on your computer.

✅ Scalable: You can upgrade as your application grows.

✅ Secure: Includes authentication, encryption, and automatic backups.

✅ Global: You can choose your server region for best performance.

2️⃣ Export Local Data with mongodump​

✅ Backup Data Locally: run the following command:

  mongodump --host localhost --port 27017 --db vibra-db --out C://Users/USER/Personal/mongodb_backups_vibra_2025

✅ Restore Data to Cloud: run the following command:

  mongorestore --uri="mongodb+srv://username:Password@cluster0xxx.xxxx.mongodb.net/" C://Users/USER/Personal/mongodb_backups_vibra_2025/

Vibra is an academic app for students who want to validate and share their thoughts and experiences with other students.