Database AI

The Database AI manages your database on MongoDB Atlas. It creates collections, builds queries, and optimizes performance.

What It Does

Database AI handles all database operations, from creating collections to writing complex aggregation pipelines.

Collections

Create and manage database collections (tables) for your data.

Users collectionProducts collectionOrders collection

Queries

Build complex queries and aggregations to retrieve data.

Filter by dateSearch text fieldsAggregate statistics

Indexes

Create indexes for faster queries on frequently accessed fields.

Email indexCompound indexesText search indexes

Security

Configure access controls and data validation rules.

User permissionsField-level securityData validation

How to Use It

Describe your data needs:

Creating collections

"Create a products collection with name, price, description, and category fields"

Queries

"Show me all orders from the last 30 days grouped by customer"

Performance

"Add an index on the email field in the users collection"

About MongoDB Atlas

Your data is stored on MongoDB Atlas, a fully managed cloud database:

  • Automatic backups — Your data is backed up daily
  • Scalable — Storage grows automatically as needed
  • Secure — Encrypted at rest and in transit
  • Global — Deploy in regions close to your users

Data Modeling

MongoDB uses flexible documents instead of rigid tables. The AI will help you design your data structure:

// Example: Product document
{
  "_id": "prod_123",
  "name": "Wireless Headphones",
  "price": 79.99,
  "category": "Electronics",
  "specs": {
    "battery": "40 hours",
    "wireless": true
  },
  "tags": ["audio", "bluetooth", "wireless"],
  "createdAt": "2024-01-15T10:30:00Z"
}

Tips for Database Design

  • Describe your data relationships — "Users have many orders, orders have many items"
  • Mention performance needs — "We'll search products by name frequently"
  • The AI will suggest appropriate indexes automatically