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JSON to SQL Schema Generator

Generate SQL CREATE TABLE statements from any JSON object.

About This Tool

Generate SQL CREATE TABLE statements from any JSON object. This tool runs entirely in your browser — no data is ever sent to a server. Free to use, no account required.

How JSON to SQL Schema Conversion Works

The tool analyzes your JSON document and infers the SQL table structure needed to store that data in a relational database.

Type Inference

String values become VARCHAR or TEXT, integers become INT, decimal numbers become DECIMAL or FLOAT, booleans become BOOLEAN. Nested objects become separate related tables, and null-able fields get a NULL modifier.

Supported SQL Dialects

Generates CREATE TABLE statements for MySQL, PostgreSQL, SQLite, and SQL Server. Switch between dialects to get syntax-appropriate output for your specific database system.

Designing a Database from JSON Data

Converting JSON to SQL schema is the first step when moving from a document-based data model to a relational one.

Normalizing Nested Objects

Nested JSON objects become separate tables linked by foreign keys. The tool generates the full CREATE TABLE chain with proper foreign key constraints, following database normalization best practices.

Handling JSON Arrays

Arrays of objects become related tables with a parent foreign key. Arrays of primitive values (like a list of tags) become a separate junction table or a comma-separated VARCHAR depending on your preference.

Frequently Asked Questions

What does JSON to SQL Schema do?

It analyzes a JSON document and generates SQL CREATE TABLE statements that could store that data in a relational database. The tool infers column names from JSON keys, column types from JSON value types (string → VARCHAR, number → INT or DECIMAL, boolean → BOOLEAN), and creates separate tables for nested objects with foreign key relationships.

Which SQL databases does the generated schema support?

The tool generates schemas for MySQL/MariaDB, PostgreSQL, SQLite, and Microsoft SQL Server. Each dialect has different data types and syntax — for example, PostgreSQL uses SERIAL for auto-increment while MySQL uses AUTO_INCREMENT. Select your target database before generating.

How are nested JSON objects handled in the SQL schema?

Nested objects are normalized into separate tables. For example, a JSON user object containing an address object produces a users table and an addresses table, with addresses.user_id as a foreign key referencing users.id. This follows relational database normalization best practices.

Can I use the generated SQL schema directly in production?

The generated schema is a starting point, not a production-ready schema. Review and customize it: add appropriate VARCHAR lengths, choose between TEXT and VARCHAR for string fields, add indexes for frequently queried columns, and add NOT NULL constraints where appropriate.

JSON to SQL Schema Generation

Generating SQL schema from JSON samples automates database design for data imports, API-to-database pipelines, and rapid prototyping.

JSON Input → SQL Schema

// JSON Sample
{
  "id": 1,
  "username": "alice_dev",
  "email": "alice@example.com",
  "age": 30,
  "score": 98.5,
  "isActive": true,
  "createdAt": "2024-01-15T10:30:00Z",
  "tags": ["admin", "user"]
}

-- Generated PostgreSQL Schema
CREATE TABLE users (
  id          SERIAL PRIMARY KEY,
  username    VARCHAR(255) NOT NULL,
  email       VARCHAR(255) NOT NULL UNIQUE,
  age         INTEGER,
  score       DECIMAL(10, 2),
  is_active   BOOLEAN DEFAULT TRUE,
  created_at  TIMESTAMP WITH TIME ZONE,
  tags        JSONB
);

SQL Type Mapping by Database

JSON Type	MySQL	PostgreSQL	SQLite	SQL Server
string	VARCHAR(255)	VARCHAR(MAX)	TEXT	NVARCHAR(255)
integer	INT	INTEGER	INTEGER	INT
float	DECIMAL(10,2)	DECIMAL(10,2)	REAL	DECIMAL(10,2)
boolean	TINYINT(1)	BOOLEAN	INTEGER	BIT
date	DATETIME	TIMESTAMP	TEXT	DATETIME2
JSON	JSON	JSONB	TEXT	NVARCHAR(MAX)

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