JSON to SQL Converter

Convert JSON data to SQL INSERT or UPDATE statements. Perfect for quickly generating SQL from API responses, JSON exports, or configuration files.

Settings

Table Name

Query Type

Primary Key Field Field to use in the WHERE clause for UPDATE statements

Database Type

Include NULL values Prettify SQL output Generate batch insert

Examples

JSON Input

SQL Output

About This JSON to SQL Converter

Our JSON to SQL converter helps you transform JSON data into SQL INSERT, UPDATE, or CREATE TABLE statements. This tool is ideal for quickly generating SQL from API responses, exported data, or configuration files.

Features

Multiple SQL dialects: Supports PostgreSQL, MySQL, SQLite, and SQL Server
Flexible output options: Create individual or batch INSERT statements
Nested data support: Converts arrays and objects to database-specific JSON types
Privacy-focused: All conversion happens client-side in your browser
Formatting options: Prettify SQL for better readability

How It Works

The tool analyzes your JSON data structure and converts it to equivalent SQL statements. For arrays of objects, it generates multiple INSERT statements (either as individual statements or as a batch). For nested data like arrays and objects, it uses database-specific JSON types like JSONB for PostgreSQL or JSON for MySQL.

When using the CREATE TABLE + INSERT option, the tool automatically generates appropriate column types based on the JSON data values, including proper handling of IDs and primary keys.

Frequently Asked Questions

Can I convert nested JSON objects to SQL?

Yes, the converter handles nested JSON objects and arrays by storing them as JSON/JSONB types in databases that support them (PostgreSQL, MySQL) or as TEXT in databases that don't have native JSON support (SQLite, older SQL Server versions).

How does the tool determine column types?

The tool analyzes the data types in your JSON and maps them to appropriate SQL types. For example:

JavaScript numbers become INT or DECIMAL
Strings become VARCHAR(255) for short strings or TEXT for longer ones
Booleans become database-specific boolean types (BOOLEAN, TINYINT, BIT)
Objects and arrays become JSON types (JSONB for PostgreSQL, JSON for MySQL)
Date strings are detected and converted to DATE or TIMESTAMP types

The tool attempts to detect primary key fields (named "id" or ending with "_id") and applies appropriate auto-increment syntax based on the selected database.

What's the difference between individual and batch inserts?

Individual inserts create separate INSERT statements for each row of data:

INSERT INTO users (id, name, email) VALUES (1, 'John', 'john@example.com');
INSERT INTO users (id, name, email) VALUES (2, 'Jane', 'jane@example.com');

Batch inserts combine all rows into a single INSERT statement with multiple value sets:

INSERT INTO users (id, name, email) VALUES 
(1, 'John', 'john@example.com'),
(2, 'Jane', 'jane@example.com');

Batch inserts are more efficient for inserting large amounts of data but may not be supported by all database clients or may have row limits in some databases.

Is my data secure when using this tool?

Yes, all conversion happens entirely in your browser. Your JSON data is never sent to our servers, making this tool completely secure for handling sensitive data.

How do I handle primary keys and auto-incrementing IDs?

When using the CREATE TABLE + INSERT option, the tool automatically detects fields named "id" or ending with "_id" and configures them as primary keys with appropriate auto-increment syntax for your selected database:

PostgreSQL: Uses SERIAL PRIMARY KEY
MySQL: Uses INT AUTO_INCREMENT PRIMARY KEY
SQL Server: Uses INT IDENTITY(1,1) PRIMARY KEY
SQLite: Uses standard INTEGER PRIMARY KEY which auto-increments by default

What's the maximum size of JSON I can convert?

Since all processing happens in your browser, the maximum size depends on your device's memory. For very large JSON files (multiple MB), you might experience slower performance. We recommend:

Breaking very large datasets into smaller chunks of a few hundred objects
Using the "Generate batch insert" option for more efficient SQL with large datasets
Disabling the "Prettify SQL output" option if you experience performance issues

Does the converter support date and time formats?

Yes, the tool detects common date formats (like ISO 8601) in your JSON strings and maps them to appropriate SQL column types:

Strings matching YYYY-MM-DD format are converted to DATE type
Strings containing both date and time components are converted to TIMESTAMP type
The data type used depends on your selected database dialect

Can I generate SQL for databases not listed in the options?

While the tool specifically optimizes for PostgreSQL, MySQL, SQLite, and SQL Server, the generated SQL is generally compatible with many other database systems. For best results:

Select the option closest to your target database
For Oracle, you can use PostgreSQL as the closest match and adjust syntax afterwards
For BigQuery, you can use MySQL as a starting point
For MariaDB, use the MySQL option as they share nearly identical syntax

You may need to make minor adjustments to the generated SQL based on your specific database's requirements.