schema.txt

Certainly! I'll provide you with a MongoDB schema design for the requirements you've described, and then I'll add some additional considerations and useful information.



// Theme Room Schema
const themeRoomSchema = {
  _id: ObjectId,
  name: String,
  description: String,
  tags: [String],
  createdAt: Date,
  updatedAt: Date
}

// Story Schema
const storySchema = {
  _id: ObjectId,
  customId: String,
  title: String,
  type: { type: String, enum: ['root', 'child'] },
  content: String,
  themeRoomId: { type: ObjectId, ref: 'ThemeRoom' },
  prev: [{ type: ObjectId, ref: 'Story' }],
  next: [{ type: ObjectId, ref: 'Story' }],
  createdAt: Date,
  updatedAt: Date
}

// User Schema
const userSchema = {
  _id: ObjectId,
  email: String,
  password: String,
  socialLinks: {
    facebook: String,
    instagram: String,
    youtube: String,
    personalWebsite: String,
    twitter: String,
    github: String
  },
  createdAt: Date,
  updatedAt: Date
}

// Comment Schema
const commentSchema = {
  _id: ObjectId,
  storyId: { type: ObjectId, ref: 'Story' },
  userId: { type: ObjectId, ref: 'User' },
  content: String,
  createdAt: Date,
  updatedAt: Date
}

// User Story Interaction Schema
const userStoryInteractionSchema = {
  _id: ObjectId,
  userId: { type: ObjectId, ref: 'User' },
  storyId: { type: ObjectId, ref: 'Story' },
  interactionType: { type: String, enum: ['like', 'dislike', 'save'] },
  createdAt: Date
}

// User Theme Room Interaction Schema
const userThemeRoomInteractionSchema = {
  _id: ObjectId,
  userId: { type: ObjectId, ref: 'User' },
  themeRoomId: { type: ObjectId, ref: 'ThemeRoom' },
  interactionType: { type: String, enum: ['favorite'] },
  createdAt: Date
}

// Story Author Schema
const storyAuthorSchema = {
  _id: ObjectId,
  storyId: { type: ObjectId, ref: 'Story' },
  userId: { type: ObjectId, ref: 'User' },
  createdAt: Date
}

// User Storyline Schema
const userStorylineSchema = {
  _id: ObjectId,
  userId: { type: ObjectId, ref: 'User' },
  name: String,
  stories: [{ type: ObjectId, ref: 'Story' }],
  createdAt: Date,
  updatedAt: Date
}


Now, let me provide some additional considerations and useful information for your database design:

1. Indexing:
   - Create indexes on frequently queried fields like `email` in the User schema, `themeRoomId` in the Story schema, and `storyId` in the Comment schema.
   - Consider compound indexes for fields that are often queried together.

2. Validation:
   - Implement schema validation using MongoDB's built-in validation features to ensure data integrity.

3. Timestamps:
   - Use MongoDB's built-in `timestamps` option to automatically manage `createdAt` and `updatedAt` fields.

4. Relationships:
   - The design uses references (`ref`) to establish relationships between documents. This allows for more flexible querying and prevents data duplication.

5. Array Fields:
   - Be cautious with array fields like `next` and `prev` in the Story schema. If these arrays grow too large, they might impact performance.

6. Denormalization:
   - Consider denormalizing some data for frequently accessed information. For example, you might want to store the author's name directly in the Story document to avoid an additional query.

7. Text Search:
   - If you plan to implement text search functionality for stories or theme rooms, consider using MongoDB's text indexes.

8. Scalability:
   - The current design should scale well, but keep an eye on the size of embedded arrays (like `likedStories` in the User schema). If they grow too large, consider using a separate collection for user interactions.

9. Security:
   - Ensure that you hash and salt passwords before storing them in the database.
   - Implement proper access controls to protect sensitive user data.

10. Aggregation Pipeline:
    - For complex queries involving multiple collections (e.g., getting a user's stories with their theme room details), utilize MongoDB's aggregation pipeline for efficient data retrieval.

11. Change Streams:
    - If real-time updates are required (e.g., for live commenting), consider using MongoDB's change streams feature.

12. Archiving:
    - As your database grows, you might want to implement an archiving strategy for old or inactive data to maintain performance.

Remember to adjust this schema based on your specific application requirements and performance needs. It's also a good practice to start with this design and iterate as you develop and test your application.