ByteJSON

SQL to Mongoose Schema Generator

Convert SQL CREATE TABLE statements to Mongoose schema definitions for MongoDB with TypeScript or JavaScript support.

Output:

What is SQL to Mongoose Schema Generator?

Mongoose is the most widely used MongoDB object modeling library for Node.js, providing a schema-based solution to model application data with built-in type casting, validation, query building, and middleware hooks. This converter takes your relational SQL CREATE TABLE definitions and produces equivalent Mongoose schema objects, bridging the gap between relational and document-oriented data modeling. Because MongoDB is a NoSQL database, the converter maps SQL column types to Mongoose SchemaTypes — for instance, VARCHAR becomes String, INTEGER becomes Number, and JSONB becomes Schema.Types.Mixed. Foreign key references are converted to ObjectId fields with ref properties, enabling Mongoose population to resolve related documents across collections.

How to Use

  1. Select whether you want TypeScript or JavaScript output from the dropdown
  2. Paste one or more SQL CREATE TABLE statements into the input editor on the left
  3. Press the Generate Mongoose Schema button to produce schema definitions for each table
  4. Review the output: TypeScript mode includes Document interfaces alongside schemas, while JavaScript mode uses module.exports
  5. Copy the generated code into your Mongoose project and adjust any schema options like timestamps or indexes as needed

Why Use This Tool?

Eliminates hours of manual schema writing by auto-generating Mongoose schemas from existing SQL definitions
Foreign key REFERENCES are converted to Schema.Types.ObjectId with ref, enabling Mongoose populate() for joins
JSONB and JSON columns map to Schema.Types.Mixed, preserving flexibility for semi-structured data in MongoDB
TypeScript output includes typed Document interfaces so your models get full IntelliSense support
Default values like NOW() are translated to Date.now, and boolean defaults map to native JavaScript booleans

Tips & Best Practices

  • Mongoose does not enforce uniqueness at the application level — add a compound index manually if you need multi-field unique constraints
  • Consider enabling the timestamps option on your schema to get automatic createdAt and updatedAt fields instead of defining them manually
  • Schema.Types.Mixed fields bypass Mongoose validation by default — use pre-save hooks if you need to validate arbitrary JSON content
  • When using ObjectId references, always call populate() in your queries to fetch related documents rather than issuing separate lookups

Frequently Asked Questions

How does the SQL-to-Mongoose type mapping work?

The converter follows Mongoose conventions: INTEGER, BIGINT, and SERIAL map to Number; VARCHAR, CHAR, and TEXT map to String; BOOLEAN maps to Boolean; TIMESTAMP and DATE map to Date; JSON and JSONB map to Schema.Types.Mixed; UUID maps to String; and BLOB maps to Buffer. Foreign key columns are overridden to Schema.Types.ObjectId with a ref property pointing to the referenced model.

When should I avoid using this converter?

If your SQL schema relies heavily on advanced relational features like many-to-many junction tables, composite primary keys, or complex CHECK constraints, the generated Mongoose schemas will need significant manual adjustment. MongoDB also does not support server-enforced foreign keys, so referential integrity must be managed in application code.

Is my SQL data sent to a server?

No. All parsing and code generation happens entirely in your browser using client-side JavaScript. Your SQL schema never leaves your device, and no network requests are made during the conversion process.

What is Schema.Types.Mixed and when should I use it?

Schema.Types.Mixed is a flexible Mongoose type that accepts any JavaScript value — objects, arrays, primitives, or null. It is used for JSON and JSONB columns because their structure is not fixed. The trade-off is that Mixed fields skip Mongoose change tracking and validation, so you must call markModified() before saving changes to these fields.

Can I customize the generated schemas?

Yes. The generated code is a starting point. You can add virtual properties, instance methods, static methods, pre/post hooks, custom validators, and schema options like timestamps, strict, or minimize. The converter handles the boilerplate so you can focus on domain-specific logic.

Real-world Examples

Migrating a PostgreSQL user accounts table to MongoDB

A startup moving from PostgreSQL to MongoDB needs to convert their users table with email uniqueness, boolean active flags, and JSONB metadata into a Mongoose schema with proper validation.

Input
CREATE TABLE users (
  id SERIAL PRIMARY KEY,
  email VARCHAR(255) UNIQUE NOT NULL,
  is_active BOOLEAN DEFAULT true,
  metadata JSONB
);
Output
const UserSchema = new Schema({
  id: { type: Number, required: true },
  email: { type: String, required: true, unique: true },
  is_active: { type: Boolean, default: true },
  metadata: { type: Schema.Types.Mixed }
}, { collection: 'users' });

Generating TypeScript models for a blog with post-author relationships

A content platform needs typed Mongoose models where posts reference the authors collection via ObjectId, enabling populate() to embed author details in query results.

Input
CREATE TABLE posts (
  id SERIAL PRIMARY KEY,
  author_id INTEGER NOT NULL REFERENCES users(id),
  title VARCHAR(255) NOT NULL,
  published BOOLEAN DEFAULT false
);
Output
interface IPosts extends Document {
  id: number;
  author_id: mongoose.Types.ObjectId;
  title: string;
  published?: boolean;
}

const PostsSchema: Schema = new Schema({
  id: { type: Number, required: true },
  author_id: { type: Schema.Types.ObjectId, required: true, ref: 'Users' },
  title: { type: String, required: true },
  published: { type: Boolean, default: false }
}, { collection: 'posts' });

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