SQL to JSON Schema Generator

The SQL to JSON Schema Generator is a powerful online tool designed for developers, database administrators, and API architects. With this tool, you can effortlessly transform raw SQL CREATE TABLE definitions into standard JSON Schema structures. This bridges the gap between relational databases and modern web APIs, where JSON Schema is extensively used for data validation.

Whether you are building REST API documentation, converting legacy applications, or writing validation rules for your frontend, manually converting SQL to JSON Schema is tedious and error-prone. Our tool handles data type mapping, recognizes NOT NULL constraints, and structures everything perfectly to Draft-07 specs.

Quick Solution

1. Copy your SQL CREATE TABLE statements containing your database structure.
2. Paste the SQL into the left-hand editor of our generator.
3. Instantly copy the resulting valid JSON Schema Draft-07 output from the right panel.

When Should I Use This?

• Migrating from SQL databases to NoSQL/document stores
• Generating API validation schemas from existing tables
• Creating TypeScript types from database schemas
• Documenting database structure as JSON Schema
• Building form validation rules from table constraints

Real-World Examples

Here is an example converting a typical SQL CREATE TABLE statement into JSON Schema:

SQL Input

CREATE TABLE users (
  id INT PRIMARY KEY,
  username VARCHAR(50) NOT NULL,
  created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
  age INT CHECK (age >= 18)
);

JSON Schema Output

{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "type": "object",
  "properties": {
    "id": {
      "type": "integer"
    },
    "username": {
      "type": "string",
      "maxLength": 50
    },
    "created_at": {
      "type": "string",
      "format": "date-time"
    },
    "age": {
      "type": "integer"
    }
  },
  "required": [
    "username"
  ]
}

How the Data Type Mapping Works

The tool uses an intelligent parsing algorithm to map SQL data types to valid JSON Schema types:

• Integers (INT, SERIAL, BIGINT) map to "type": "integer".
• Decimals (DECIMAL, FLOAT, NUMERIC) map to "type": "number".
• Booleans (BOOLEAN, BOOL) map to "type": "boolean".
• Strings (VARCHAR, TEXT, CHAR) map to "type": "string".
• Dates (TIMESTAMP, DATE) map to "type": "string" with "format": "date-time" or "date".
• JSON (JSON, JSONB) maps to "type": "object".

Need to format complex DDL files first? Clean your SQL with our SQL formatter. Once generated, verify payloads using our JSON schema validator or transform models across formats with our JSON to JSON schema tool. Need deeper architectural rules? Read our complete guide to JSON schema validation.

Deep Dive: SQL DDL vs JSON Schema Draft-07 Architecture

Translating relational SQL Data Definition Language (DDL) statements into document-oriented JSON Schema definitions requires balancing strict type safety with the flexibility of JSON. In standard SQL databases like PostgreSQL, MySQL, and Microsoft SQL Server, data types are enforced strictly at the storage engine level. For example, a VARCHAR(255) column rejects strings exceeding 255 characters, and a NOT NULL constraint immediately terminates transaction inserts that omit the field.

In contrast, JSON Schema draft-07 operates on structural validation semantics over serialized JSON payloads. When converting DDL to draft-07 schemas, several structural conversions occur:

• Character Length Constraints: SQL VARCHAR(N) or CHAR(N) specifications are translated into JSON Schema string properties equipped with explicit "maxLength": N attributes, preserving exact domain boundaries.
• Numeric Precision & Scale: SQL decimal declarations such as DECIMAL(10,2) or NUMERIC(12,4) map to JSON Schema "type": "number", while auto-incrementing surrogate keys (SERIAL, BIGSERIAL, AUTO_INCREMENT) map to "type": "integer" with a "minimum": 1 constraint.
• Nullability & Required Arrays: Unlike SQL where nullability is a column-level property (NULL vs NOT NULL), JSON Schema separates field presence from nullability. When our parser encounters a NOT NULL declaration, it pushes the column name into the root schema's "required": [...] array. If a column allows nulls, the JSON Schema property definition receives a union type declaration: "type": ["string", "null"].
• Default Values: SQL defaults such as DEFAULT 'active' or DEFAULT 0 are extracted and embedded into the corresponding JSON property using the draft-07 "default" keyword, ensuring frontend form builders and mock generators respect initial database assumptions.

Integrating automated DDL-to-JSON Schema pipelines into your CI/CD workflow guarantees that API documentation, frontend input validation models, and backend database contracts never drift out of sync during rapid development iterations.

Best Practices

When generating JSON schemas from SQL, ensure your DDL statements are syntactically valid and terminated with semicolons. If you are using this alongside other data-conversion workflows, always verify the required fields and ensure the logical constraints of your schema match your application's expectations.

Troubleshooting

If your JSON schema is not generating correctly, check for missing commas or unclosed parentheses in your SQL CREATE TABLE statements. For advanced data types (like custom ENUMs), you may need to manually adjust the JSON schema after generation, as this tool primarily targets standard data types. Ensure your SQL does not contain complex triggers or unsupported functional constraints inside the column definitions. If parsing completely fails, try simplifying your SQL down to the core column declarations.

Why Privacy Matters

Your data privacy is our top priority. Database schemas often reveal proprietary business logic and internal architectural designs. This tool is 100% private — your data never leaves your browser. We do not track, store, or transmit your database schemas, table names, or structures to any external servers. All processing is executed client-side.

Browser Compatibility

Our SQL to JSON Schema generator uses standard Web APIs and is fully functional on all modern web browsers including Google Chrome, Mozilla Firefox, Apple Safari, and Microsoft Edge. No additional plugins or downloads are required. Mobile browsers are also fully supported with an optimized layout for viewing and copying code on smaller screens.