JSON to SQL — Generate SQL Statements

Convert JSON to SQL CREATE TABLE and INSERT statements. Supports MySQL, PostgreSQL, and SQLite.

JSON Input

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SQL Output

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About JSON to SQL Generator

Converting JSON data to SQL statements is a common task when importing API responses, configuration data, or NoSQL exports into relational databases. Our JSON to SQL generator analyzes your JSON structure, infers appropriate SQL column types, and produces ready-to-run CREATE TABLE and INSERT INTO statements for MySQL, PostgreSQL, or SQLite. Whether you are migrating data from a document database, seeding a test environment, or prototyping a schema from sample data, this tool saves you from writing boilerplate SQL by hand.

How to Use JSON to SQL Generator

1

Paste or Upload JSON Data

Paste a JSON array of objects (each object represents a row) or a single JSON object into the editor. You can also drag and drop a .json file directly.

2

Choose SQL Dialect and Table Name

Select your target database dialect — MySQL, PostgreSQL, or SQLite — and enter a custom table name. The generator adjusts quoting, type mappings, and syntax for your chosen dialect.

3

Copy the Generated SQL

Review the CREATE TABLE and INSERT INTO statements in the output panel. Copy the SQL to your clipboard or download it as a .sql file, ready to execute in your database client.

Common Use Cases

API Data Import

Convert REST API JSON responses into SQL INSERT statements for importing data into your relational database. Ideal for one-time data loads from third-party APIs or internal microservices.

Database Schema Prototyping

Generate CREATE TABLE statements from sample JSON data to quickly prototype database schemas that match your data structure. Iterate on your schema design without writing SQL from scratch.

NoSQL to SQL Migration

Convert MongoDB documents, Firebase Firestore exports, DynamoDB items, or other NoSQL JSON data into SQL for migration to PostgreSQL, MySQL, or SQLite relational databases.

Test Data Seeding

Generate SQL INSERT statements from JSON test fixtures to seed development and staging databases quickly. Keep your test data in version-controlled JSON files and generate SQL on demand.

Data Analysis Preparation

Import JSON datasets into a SQL database for running analytical queries, joins, and aggregations that would be difficult to perform directly on JSON files.

ETL Pipeline Prototyping

Use generated SQL as a starting point for ETL (Extract, Transform, Load) pipelines. Review the inferred schema, add constraints and indexes, then integrate into your data pipeline.

Why Use Our JSON to SQL Generator?

Multi-Dialect Support - Generate syntactically correct SQL for MySQL, PostgreSQL, or SQLite with proper identifier quoting and type mappings for each
Smart Type Inference - Automatically detects integers, floats, booleans, strings, and null values from your JSON data and maps them to appropriate SQL column types
Instant Generation - Paste JSON and get production-ready CREATE TABLE and INSERT statements in milliseconds, no server round-trip required
Handles Complex Arrays - Arrays of objects with inconsistent keys are merged into a unified schema, with missing fields handled gracefully as NULL
Zero Configuration - Works out of the box with sensible defaults; just paste JSON and pick your dialect
Privacy-First - All SQL generation happens in your browser; your data is never uploaded to any server

Key Features

MySQL, PostgreSQL, and SQLite dialect support

Automatic column type inference (INT, VARCHAR, TEXT, BOOLEAN, DOUBLE/REAL)

CREATE TABLE statement generation with proper column definitions

INSERT INTO statement generation with escaped values

Configurable table name

Handles arrays of objects — each object becomes a row

Proper identifier quoting per dialect (backticks for MySQL, double quotes for PostgreSQL/SQLite)

Nested objects and arrays stored as TEXT/JSON columns

File upload with drag & drop support

One-click copy and .sql file download

100% Client-Side Processing

Your data never leaves your browser

No Server UploadJSON processed locally
Works OfflinePWA installed
100% PrivateZero data collection

All processing happens in your browser using JavaScript. Your data is never sent to our servers or any third party. Safe for sensitive data, API keys, and production configs.

Frequently Asked Questions

Quick answers to common questions about json to sql generator


Strings map to VARCHAR(255) or TEXT depending on length, integers to INT/INTEGER, decimal numbers to DOUBLE (MySQL) or REAL (SQLite) or DOUBLE PRECISION (PostgreSQL), booleans to BOOLEAN (PostgreSQL/SQLite) or TINYINT(1) (MySQL), and null values default to TEXT. Nested objects and arrays are serialized as JSON strings and stored in TEXT columns.


Yes! If your JSON is an array of objects, each object becomes a row in the INSERT statement. All unique keys found across all objects become columns in the CREATE TABLE statement. Objects missing certain keys will have NULL values for those columns.


MySQL uses backtick quoting for identifiers and TINYINT(1) for booleans. PostgreSQL uses double-quote quoting, native BOOLEAN type, and DOUBLE PRECISION for decimals. SQLite uses double-quote quoting, simpler types like TEXT and REAL, and is more lenient with type affinity. Each dialect produces syntactically correct SQL for its target database.


Nested objects and arrays are serialized as JSON strings and stored in TEXT columns. The tool does not automatically create separate tables for nested data. For fully normalized schemas with foreign keys and separate tables, you would need to manually refactor the generated SQL.


The generated SQL is syntactically correct and values are properly escaped to prevent SQL injection. However, for production use you should review the inferred column types, add primary keys (AUTO_INCREMENT or SERIAL), create indexes for frequently queried columns, add NOT NULL constraints, and define foreign key relationships as needed.


The generator scans all objects in the array and collects every unique key to build the column list. Objects that are missing a particular key will have NULL inserted for that column. This means you get a complete, unified schema even if your JSON data is not perfectly consistent.


Yes. Since processing happens entirely in your browser, the tool can handle large JSON arrays with thousands of objects. Performance depends on your device, but most datasets generate SQL in under a second. For very large datasets (100K+ rows), consider using a dedicated ETL tool or scripting the import.


In PostgreSQL and SQLite, boolean JSON values (true/false) map to the native BOOLEAN type and are inserted as TRUE/FALSE. In MySQL, booleans are stored as TINYINT(1) with values 1 and 0, since MySQL does not have a true boolean type. The generator handles this dialect difference automatically.