About JSON to SQL Converter

Transform complex JSON data structures into normalized SQL database schemas with our free online converter. Our tool intelligently handles nested objects, arrays, and complex data hierarchies, automatically generating CREATE TABLE (DDL) and INSERT (DML) statements optimized for MySQL, PostgreSQL, MariaDB, and Oracle databases. Perfect for API data migration, NoSQL to SQL conversion, and modernizing legacy data systems.

How to Use the JSON to SQL Converter

1. Paste or upload your JSON data: Copy your JSON content into the editor, upload a .json file, or try our sample nested data to see the normalization in action.
2. Select your target database: Choose between PostgreSQL, MySQL, or MariaDB to ensure the generated SQL uses the correct syntax and data types for your database.
3. Configure normalization: Enable "Normalize JSON Structure" to automatically flatten nested objects and arrays into separate related tables with foreign keys.
4. Customize advanced options (optional): Set primary key columns, ignore specific fields, rename columns, or use native JSON types for databases that support them.
5. Generate SQL: Click "Convert to SQL" to instantly generate a complete SQL schema with CREATE TABLE statements and INSERT commands for all your JSON data.

Key Features

• JSON Normalization: Automatically flatten nested objects and arrays into properly normalized relational tables
• Multi-Database Support: Generate SQL for PostgreSQL, MySQL, MariaDB, and Oracle databases
• Nested Object Handling: Intelligently process complex hierarchical JSON structures
• Array Support: Convert JSON arrays into separate tables with proper relationships
• Native JSON Type: Option to use native JSON/JSONB columns for PostgreSQL and MySQL 5.7+
• Free, No Signup Required: Use all features without creating an account or paying
• Browser-Based Processing: Your data stays private - all processing happens locally in your browser
• Test SQL Instantly: Run generated SQL directly in our online SQL environment

Example: JSON to SQL Conversion with Normalization

Input JSON (with nested data):

[
  {"id": 1,
    "name": "John Doe",
    "email": "john.doe@example.com",
    "address": {"city": "New York", "country": "USA"}},
  {"id": 2,
    "name": "Jane Smith",
    "email": "jane.smith@example.com",
    "address": {"city": "Los Angeles", "country": "USA"}}
]

Generated SQL Output (PostgreSQL - Normalized):

CREATE TABLE main_table (
    id NUMERIC,
    name TEXT,
    email TEXT
);

CREATE TABLE main_table_address (
    main_table_id NUMERIC,
    city TEXT,
    country TEXT,
    FOREIGN KEY (main_table_id) REFERENCES main_table(id)
);

INSERT INTO main_table (id, name, email)
VALUES (1, 'John Doe', 'john.doe@example.com');

INSERT INTO main_table_address (main_table_id, city, country)
VALUES (1, 'New York', 'USA');

INSERT INTO main_table (id, name, email)
VALUES (2, 'Jane Smith', 'jane.smith@example.com');

INSERT INTO main_table_address (main_table_id, city, country)
VALUES (2, 'Los Angeles', 'USA');

Frequently Asked Questions

Technical Details

Understanding how our JSON to SQL converter processes your data:

• Generates normalized SQL schema by default to eliminate data redundancy
• Numeric values are mapped to numeric SQL datatype for precision
• Text values are mapped to text datatype for flexibility
• Nested objects become separate tables with foreign key constraints
• Arrays are converted to child tables with one-to-many relationships
• You can specify a custom primary key column in Advanced Options
• Column names are automatically sanitized to comply with SQL naming conventions
• Check out the detailed tutorial and examples here