MongoDB Mock Data Generator (Supports ObjectId, ISODate, Native Shell Scripts)
Generate production-ready MongoDB mock data with native ObjectId, ISODate wrappers, and MongoDB shell script format ready for MongoDB Shell or Compass.
Why MongoDB Developers Choose MockBlast
Most mock data generators output JSON that loses MongoDB's native data types. MockBlast generates true MongoDB shell scripts with proper type wrappers:
🆔 Native ObjectId Support
Generate valid MongoDB ObjectIds (24-character hex strings) wrapped with ObjectId(). MockBlast detects _id fields automatically and generates proper MongoDB IDs, not UUIDs or strings.
📅 ISODate Wrappers
All date and datetime fields are wrapped with ISODate() to preserve MongoDB's date type. Unlike plain JSON imports, your dates remain as Date objects, not strings.
📜 MongoDB Shell Scripts
Generate db.collection.insertMany([...]) scripts ready to run in MongoDB Shell or Compass. No conversion needed—copy, paste, execute.
🔗 Embedded Documents & Arrays
Support for nested objects and arrays. MockBlast generates proper JSON structures that MongoDB accepts, including embedded documents and arrays of values.
MongoDB-Specific Features
MockBlast understands MongoDB's document model and data types:
- •ObjectId Generation: Native 24-character hex ObjectIds wrapped with ObjectId() for _id fields and references.
- •ISODate Wrappers: Date and datetime fields wrapped with ISODate() to preserve MongoDB's Date type.
- •Shell Script Format: db.collection.insertMany([...]) syntax ready for MongoDB Shell or Compass.
- •Embedded Documents: Support for nested objects and arrays, perfect for MongoDB's flexible schema.
- •Type Preservation: Unlike JSON imports, MockBlast preserves MongoDB data types (ObjectId, Date, Number, Boolean).
- •Collection Names: Use your table names as MongoDB collection names automatically.
Example: MongoDB Schema with ObjectId and ISODate
Import This Schema (SQL format):
CREATE TABLE users ( _id VARCHAR(24) PRIMARY KEY, name VARCHAR(100) NOT NULL, email VARCHAR(100) UNIQUE NOT NULL, created_at TIMESTAMP DEFAULT NOW() ); CREATE TABLE posts ( _id VARCHAR(24) PRIMARY KEY, user_id VARCHAR(24), title VARCHAR(200), content TEXT, created_at TIMESTAMP DEFAULT NOW() );
MockBlast Generates 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") },
{ "_id": ObjectId("65a1b2c3d4e5f6789012345b"), "name": "Jane Smith", "email": "jane@example.com", "created_at": ISODate("2024-01-16T14:20:00.000Z") }
]);
db.posts.insertMany([
{ "_id": ObjectId("65a1b2c3d4e5f6789012345c"), "user_id": ObjectId("65a1b2c3d4e5f6789012345a"), "title": "Getting Started with MongoDB", "content": "Lorem ipsum...", "created_at": ISODate("2024-01-17T08:15:00.000Z") }
]);Copy and paste this directly into MongoDB Shell (mongosh) or MongoDB Compass. The ObjectId() and ISODate() wrappers ensure proper data types.
Common MongoDB Use Cases
🧪 Testing & Development
Generate realistic test data for local MongoDB development. Seed your collections with thousands of documents to test queries, aggregation pipelines, and indexes.
🎨 UI/UX Demos
Create demo data for client presentations. Generate realistic users, products, orders, and more to showcase your MongoDB-powered application.
⚡ Performance Testing
Test aggregation pipelines, indexes, and query performance with millions of documents. MockBlast generates large MongoDB datasets quickly.
🔗 Document References
Test document relationships and references with ObjectId foreign keys. MockBlast maintains referential integrity across collections automatically.
How to Generate MongoDB Mock Data
- 1.Import Your Schema: Paste your CREATE TABLE statement (or define fields manually). MockBlast detects _id fields and date fields automatically.
- 2.Select MongoDB Format: Choose "MongoDB (JS Script)" from the format dropdown. MockBlast will generate shell scripts with ObjectId() and ISODate() wrappers.
- 3.Set Document Count: Choose how many documents to generate. MockBlast handles everything from 10 documents to 1 million+.
- 4.Download & Execute: Get MongoDB shell scripts ready to run. Copy and paste directly into MongoDB Shell (mongosh) or MongoDB Compass.
Related Resources
Foreign Keys & Referential Integrity
Learn how to generate MongoDB mock data with ObjectId references and maintain referential integrity across collections.
MongoDB Seed Data Generator
Generate MongoDB seed data with native ObjectId and ISODate wrappers. Create production-ready db.collection.insertMany() 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
- Does MockBlast support MongoDB ObjectId generation?
- Yes! MockBlast generates native MongoDB ObjectIds (24-character hex strings) and wraps them with ObjectId() in the shell script format. Perfect for MongoDB's default ID system.
- Can I generate ISODate wrappers for MongoDB dates?
- Absolutely! MockBlast automatically wraps date and datetime fields with ISODate() in MongoDB format. This preserves data types when importing into MongoDB, unlike plain JSON which converts dates to strings.
- What format does MockBlast generate for MongoDB?
- MockBlast generates native MongoDB shell scripts in the format db.collection.insertMany([...]). You can copy-paste these directly into MongoDB Shell (mongosh) or MongoDB Compass. The scripts include ObjectId() and ISODate() wrappers for proper type preservation.
- Can I import SQL schemas and convert them to MongoDB?
- Yes! MockBlast's SQL parser understands table schemas and can convert them to MongoDB format. Fields named _id are automatically detected and generated as ObjectId. Date fields are wrapped with ISODate().
- How large can MongoDB datasets be?
- MockBlast can generate millions of documents for MongoDB in seconds using server-side streaming. Perfect for seeding large MongoDB databases or testing aggregation pipelines and performance.