JSON to SQL

Generate SQL INSERT statements and CREATE TABLE DDL from a JSON array.

INSERT statements CREATE TABLE MySQL / PostgreSQL Free

Table name: Dialect: Include CREATE TABLE

Input JSON array

Ready

SQL output

JSON to SQL — Loading API Data into a Database

APIs deliver data as JSON. Databases store data as rows and columns. JSON to SQL conversion is the bridge — transforming array of objects into INSERT statements that populate database tables. Whether you're seeding a development database, migrating data between systems, or loading an API response for analysis, generated SQL saves hours of manual work.

Type inference from JSON

JSON's type system maps to SQL types predictably. JSON booleans become BOOLEAN or TINYINT(1) depending on the database. JSON integers become INT. JSON floats become DECIMAL(10,4). JSON strings that match date patterns (2023-11-14) become DATE. ISO datetime strings become DATETIME or TIMESTAMP. Nested objects and arrays, which have no SQL equivalent, are serialized as JSON strings in TEXT columns.

Generated CREATE TABLE statement

The converter generates both DDL (the table structure) and DML (the INSERT statements). The CREATE TABLE statement uses column names directly from your JSON keys — invalid SQL identifiers (spaces, special characters) are sanitized. The statement includes appropriate data types inferred from your data. You can run this directly in MySQL Workbench, pgAdmin, SQLite Browser, or any SQL client.

SQL injection prevention

String values in the generated INSERT statements are escaped using standard SQL escaping — single quotes within values are doubled (' becomes ''). This is correct for static SQL generation. However, for production application code, always use parameterized queries instead of building SQL strings from user data, regardless of escaping.

Frequently asked questions

What JSON format is required?

A flat array of objects: [{"name":"Alice","age":28}]. Each object becomes one INSERT row. All objects should have the same keys for consistent column mapping.

How are data types inferred?

JSON booleans → BOOLEAN/TINYINT, JSON numbers → INT or DECIMAL, JSON strings → VARCHAR(255), JSON null → NULL, JSON objects/arrays → TEXT (serialized as JSON string).

What is the difference between MySQL, PostgreSQL, and SQLite output?

Mainly quoting style and data types. MySQL uses backticks for identifiers, PostgreSQL uses double quotes, SQLite is more flexible. Boolean types also differ — MySQL uses TINYINT(1), PostgreSQL has a native BOOLEAN, SQLite stores as INTEGER.

How do I prevent SQL injection in the output?

This tool escapes single quotes in string values by doubling them (standard SQL escaping). For production use, always use parameterized queries in your application code — never build SQL strings from user input.

Is there a row limit?

No hard limit. For very large datasets, the output may be large — consider batching your INSERT statements into transactions for better database performance.

Is my data safe?

Yes. All SQL generation runs locally in your browser. No data is sent to any server.