MongoDB Seed Data Generator (ObjectId, ISODate, Shell Scripts)
Generate MongoDB seed data with native ObjectId and ISODate wrappers. Create production-ready db.collection.insertMany() scripts for MongoDB Shell and Compass.
Why Use MockBlast for MongoDB Seed Data?
Seeding MongoDB databases requires proper data types. MockBlast generates native MongoDB shell scripts that preserve types:
- •Type Preservation: ObjectId() and ISODate() wrappers ensure MongoDB recognizes IDs and dates correctly, not as strings.
- •Ready to Execute: db.collection.insertMany() scripts work directly in MongoDB Shell or Compass—no manual conversion needed.
- •Realistic Data: Generate realistic names, emails, addresses, and more that match production patterns.
- •Scalable: Generate thousands or millions of documents efficiently using server-side streaming.
MongoDB Seed Data Features
Native MongoDB Support
ObjectId Generation
- • 24-character hex ObjectIds
- • Automatic _id field detection
- • ObjectId() wrapper in scripts
- • Referential integrity support
Date Handling
- • ISODate() wrappers
- • Date and datetime support
- • Timezone-aware dates
- • Realistic date ranges
Document Structure
- • Embedded documents
- • Arrays of values
- • Nested objects
- • Flexible schema support
Shell Scripts
- • db.collection.insertMany()
- • MongoDB Shell compatible
- • Compass compatible
- • Atlas compatible
Example: MongoDB Seed Data Output
Generated MongoDB Shell Script:
db.users.insertMany([
{ "_id": ObjectId("65a1b2c3d4e5f6789012345a"), "name": "John Doe", "email": "john@example.com", "created_at": ISODate("2024-01-15T10:30:00.000Z"), "is_active": true },
{ "_id": ObjectId("65a1b2c3d4e5f6789012345b"), "name": "Jane Smith", "email": "jane@example.com", "created_at": ISODate("2024-01-16T14:20:00.000Z"), "is_active": true },
{ "_id": ObjectId("65a1b2c3d4e5f6789012345c"), "name": "Bob Johnson", "email": "bob@example.com", "created_at": ISODate("2024-01-17T08:15:00.000Z"), "is_active": false }
]);
db.products.insertMany([
{ "_id": ObjectId("65a1b2c3d4e5f6789012345d"), "name": "Laptop", "price": 1299.99, "category": "Electronics", "in_stock": true, "created_at": ISODate("2024-01-10T12:00:00.000Z") },
{ "_id": ObjectId("65a1b2c3d4e5f6789012345e"), "name": "Mouse", "price": 29.99, "category": "Electronics", "in_stock": true, "created_at": ISODate("2024-01-11T09:30:00.000Z") }
]);
db.orders.insertMany([
{ "_id": ObjectId("65a1b2c3d4e5f6789012345f"), "user_id": ObjectId("65a1b2c3d4e5f6789012345a"), "product_id": ObjectId("65a1b2c3d4e5f6789012345d"), "quantity": 1, "total": 1299.99, "created_at": ISODate("2024-01-18T15:45:00.000Z") }
]);This script can be executed directly in MongoDB Shell or Compass. Notice how ObjectId() and ISODate() preserve data types, and user_id references maintain referential integrity.
Best Practices for MongoDB Seed Data
1. Use ObjectId for _id Fields
Always use the ObjectId type for MongoDB _id fields. MockBlast automatically detects _id columns and generates proper ObjectIds with ObjectId() wrappers. This ensures compatibility with MongoDB's default ID system.
2. Wrap Dates with ISODate
Use ISODate() wrappers for all date fields. MockBlast automatically wraps date and datetime fields, preserving MongoDB's Date type. This allows proper date queries and sorting in MongoDB.
3. Maintain Referential Integrity
When seeding related collections, ensure parent collections are seeded first. MockBlast handles this automatically by generating parent collections before child collections, maintaining ObjectId references correctly.
4. Test with Various Document Counts
Generate different amounts of seed data for different scenarios. Small datasets (100-1,000 documents) for unit tests, medium datasets (10,000-100,000 documents) for integration tests, and large datasets (1M+ documents) for performance testing.
Importing Seed Data into MongoDB
Once you've generated your MongoDB seed data with MockBlast:
- 1.Download the MongoDB shell script file from MockBlast
- 2.Connect to your MongoDB instance using MongoDB Shell (mongosh) or MongoDB Compass
- 3.Copy and paste the db.collection.insertMany([...]) scripts into your MongoDB client
- 4.Execute the scripts. The ObjectId() and ISODate() wrappers ensure proper data types are imported
- 5.Verify the data was inserted correctly with a find() query:
db.users.find()
Related Resources
Foreign Keys & Referential Integrity
Learn how to generate MongoDB seed data with ObjectId references and maintain referential integrity across collections.
MongoDB Mock Data Generator
Generate production-ready MongoDB mock data with native ObjectId, ISODate wrappers, and MongoDB shell scripts.
How to Generate MongoDB Seed Data
Step-by-step guide to generating realistic MongoDB seed data with ObjectId, ISODate, and shell script format.
PostgreSQL Mock Data Generator
Generate production-ready PostgreSQL mock data with full support for JSONB, UUID, arrays, and foreign keys.
Frequently Asked Questions
- What makes MockBlast's MongoDB seed data different from JSON?
- MockBlast generates native MongoDB shell scripts with ObjectId() and ISODate() wrappers. Unlike plain JSON, this preserves MongoDB's data types. Dates remain as Date objects, and IDs are proper ObjectIds, not strings.
- Can I seed multiple MongoDB collections at once?
- Yes! MockBlast supports multi-table schemas that convert to multiple MongoDB collections. Each collection gets its own db.collection.insertMany() script with proper ObjectId references between collections.
- How do I use the generated MongoDB seed scripts?
- Simply copy the generated db.collection.insertMany([...]) script and paste it into MongoDB Shell (mongosh) or MongoDB Compass. The scripts are ready to execute immediately—no conversion needed.
- Does MockBlast handle MongoDB ObjectId references?
- Yes! When you have foreign key relationships in your schema, MockBlast generates ObjectId references between documents. Parent documents are created first, then child documents reference valid parent ObjectIds.
- Can I generate seed data for MongoDB Atlas?
- Absolutely! The generated MongoDB shell scripts work with MongoDB Atlas, MongoDB Community Edition, and any MongoDB-compatible database. Just connect to your Atlas cluster and run the scripts.