What SQL statements can be converted to JSON?

This tool converts three types of SQL statements: INSERT INTO (becomes an array of row objects), CREATE TABLE (becomes a schema definition with column names, types, and constraints), and SELECT (becomes a query descriptor with columns, table, WHERE, ORDER BY, and LIMIT). Each statement type produces a different JSON structure optimized for its use case.

How are SQL data types mapped to JSON?

SQL types are automatically mapped: INTEGER/DECIMAL numbers become JSON numbers, TRUE/FALSE become JSON booleans, NULL becomes JSON null, and string values (in single or double quotes) become JSON strings. Date strings remain as strings in ISO format. This preserves type information when migrating from SQL to JSON-based systems.

Can I convert INSERT statements with multiple rows?

Yes. Multi-row INSERT statements like INSERT INTO table (a, b) VALUES (1, 2), (3, 4), (5, 6) are fully supported. Each VALUES group becomes a separate JSON object in the output array. Column names from the INSERT become object keys. This is useful for bulk data export from SQL to JSON.

What is the difference between SQL to JSON and CSV to JSON?

SQL to JSON preserves the SQL structure (table name, column types, constraints) and handles SQL-specific syntax (quoted strings, NULL, booleans). CSV to JSON only converts tabular data without type information — everything is a string unless you add type inference. SQL to JSON is better when you need to preserve schema information or convert INSERT statements.

How do I convert JSON back to SQL?

Use a JSON to SQL or CSV to SQL converter. The JSON array of objects can be converted back to INSERT statements by using column names as keys and values as SQL values. For schema conversion, map JSON types back to SQL column types. This tool's companion CSV to SQL tool handles the reverse direction for tabular data.

Why convert SQL to JSON?

Common reasons: migrating data from relational databases to NoSQL stores (MongoDB, Firebase), creating API mock data from existing database records, documenting table schemas as JSON for API documentation, converting SQL dumps to JSON for data analysis tools, and building seed data files for testing environments.

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SQL to JSON Converter

SQL to JSON converts SQL statements into structured JSON objects. INSERT INTO statements become arrays of row objects with typed values (numbers, booleans, null preserved). CREATE TABLE becomes a schema definition with column names, types, and constraints. SELECT queries become query descriptor objects with columns, table, WHERE, ORDER BY, and LIMIT. Useful for migrating data from SQL databases to JSON APIs and NoSQL stores.

Convert SQL statements to JSON. INSERT INTO statements become arrays of typed row objects. CREATE TABLE becomes a schema definition with columns and constraints. SELECT queries become query descriptor objects. Auto-detects types (numbers, booleans, null). Pretty print or compact output.

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Presets

Options

Pretty print

SQL Input

JSON Output

SQL to JSON Conversion Reference

SQL Statement	JSON Output	Use Case
INSERT INTO	Array of row objects	Migrate data from SQL to JSON API
CREATE TABLE	Schema definition object	Document table structure as JSON
SELECT	Query descriptor object	Convert query to API filter format
VALUES	Auto-typed (number, bool, null)	Preserves SQL types in JSON
Multiple rows	Array of objects with column keys	Batch data export

How to Use

1
Paste your SQL statement
Paste an INSERT INTO, CREATE TABLE, or SELECT statement. Or click a preset to load sample SQL.
2
Configure output format
Toggle Pretty Print on for readable, indented JSON or off for compact single-line output.
3
Click Convert to JSON
The SQL is parsed and converted to structured JSON. INSERT rows become object arrays, CREATE TABLE becomes a schema, SELECT becomes a query descriptor.
4
Copy the result
Click Copy to copy the JSON output. Use it in your API, config file, or data migration pipeline.

Frequently Asked Questions

What SQL statements can be converted to JSON?: This tool converts three types of SQL statements: INSERT INTO (becomes an array of row objects), CREATE TABLE (becomes a schema definition with column names, types, and constraints), and SELECT (becomes a query descriptor with columns, table, WHERE, ORDER BY, and LIMIT). Each statement type produces a different JSON structure optimized for its use case.
How are SQL data types mapped to JSON?: SQL types are automatically mapped: INTEGER/DECIMAL numbers become JSON numbers, TRUE/FALSE become JSON booleans, NULL becomes JSON null, and string values (in single or double quotes) become JSON strings. Date strings remain as strings in ISO format. This preserves type information when migrating from SQL to JSON-based systems.
Can I convert INSERT statements with multiple rows?: Yes. Multi-row INSERT statements like INSERT INTO table (a, b) VALUES (1, 2), (3, 4), (5, 6) are fully supported. Each VALUES group becomes a separate JSON object in the output array. Column names from the INSERT become object keys. This is useful for bulk data export from SQL to JSON.
What is the difference between SQL to JSON and CSV to JSON?: SQL to JSON preserves the SQL structure (table name, column types, constraints) and handles SQL-specific syntax (quoted strings, NULL, booleans). CSV to JSON only converts tabular data without type information — everything is a string unless you add type inference. SQL to JSON is better when you need to preserve schema information or convert INSERT statements.
How do I convert JSON back to SQL?: Use a JSON to SQL or CSV to SQL converter. The JSON array of objects can be converted back to INSERT statements by using column names as keys and values as SQL values. For schema conversion, map JSON types back to SQL column types. This tool's companion CSV to SQL tool handles the reverse direction for tabular data.
Why convert SQL to JSON?: Common reasons: migrating data from relational databases to NoSQL stores (MongoDB, Firebase), creating API mock data from existing database records, documenting table schemas as JSON for API documentation, converting SQL dumps to JSON for data analysis tools, and building seed data files for testing environments.