JSON to SQL Converter Online — Free INSERT & CREATE TABLE

Free online JSON to SQL converter. Paste a JSON array or object and instantly generate SQL CREATE TABLE DDL with auto-inferred column types (VARCHAR, BIGINT, BOOLEAN, TEXT) plus batched INSERT statements. Supports PostgreSQL, MySQL, SQLite, and SQL Server dialects. Options for upsert mode, null handling, and batch size. No data is ever sent to a server — runs entirely in your browser.

JavaScript is required to use this interactive tool. Please enable JavaScript in your browser, or use our JSON to SQL Converter API for programmatic access.

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How to JSON to SQL Converter Online

Paste or type your JSON object or array into the input panel on the left.
Select your target SQL dialect from the dropdown — PostgreSQL, MySQL, SQLite, or SQL Server.
Configure options such as table name, batch insert size, and whether to generate UPSERT statements.
Click "Convert" or press ⌘↵ to generate the SQL DDL and INSERT statements.
Copy the output with ⌘⇧C or download it as a .sql file for use in your database client.

JSON to SQL Converter Features

Supports four major SQL dialects: PostgreSQL, MySQL, SQLite, and SQL Server with dialect-specific syntax
Automatically infers column types from JSON values — INTEGER, BIGINT, NUMERIC, BOOLEAN, TEXT, and TIMESTAMP
Generates CREATE TABLE DDL with appropriate constraints and column definitions
Produces batched INSERT statements configurable by row count for optimal import performance
Optional UPSERT mode (INSERT … ON CONFLICT / INSERT … ON DUPLICATE KEY UPDATE) for idempotent imports
Handles nested JSON objects by flattening them into dot-separated column names
Detects JSON arrays and maps them to TEXT columns with JSON serialization
Proper NULL handling — JSON null values map to SQL NULL, respecting NOT NULL constraints
Processes arrays of objects to derive a unified schema from all rows
Runs entirely in your browser — your data is never uploaded to any server
Keyboard shortcut ⌘↵ to convert instantly, ⌘⇧C to copy output
Shareable URLs encode your input and options for easy collaboration
AI-powered explanations help you understand generated SQL and type inference decisions

Supported Formats & Dialects

The JSON to SQL Converter supports 4 syntax formats and dialects for accurate parsing and processing.

PostgreSQL: Uses SERIAL/BIGSERIAL for auto-increment, native BOOLEAN type, JSONB for nested structures, and INSERT … ON CONFLICT DO UPDATE for upserts.
MySQL: Uses AUTO_INCREMENT, TINYINT(1) for booleans, TEXT for long strings, and INSERT … ON DUPLICATE KEY UPDATE for upsert operations.
SQLite: Uses INTEGER PRIMARY KEY AUTOINCREMENT, dynamic typing (no strict BOOLEAN column), and TEXT for most string and JSON values.
SQL Server: Uses IDENTITY(1,1) for auto-increment, BIT for booleans, NVARCHAR(MAX) for Unicode strings, and MERGE statements for upserts.

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All Standards

SQL (Structured Query Language)Database

SQL is the domain-specific standard language used to query, manipulate, and manage relational database management systems (RDBMS).

Pre-built Automation Pipelines

Chain JSON to SQL Converter with other utilities in a multi-step visual workflow.

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Decode a Base64 string and pretty-print the JSON inside it.

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JSON Format → TypeScript Schema

Format JSON and generate TypeScript/Zod schema from it.

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Example Input & Output

Sample Reference

Interactive Example: JSON to SQL Converter in Action

Show example

Sample Input (text)

[
  {
    "id": 1,
    "name": "Alice",
    "email": "[email protected]",
    "age": 30,
    "active": true
  },
  {
    "id": 2,
    "name": "Bob",
    "email": "[email protected]",
    "age": null,
    "active": false
  },
  {
    "id": 3,
    "name": "Charlie",
    "email": "[email protected]",
    "age": 25,
    "active": true
  }
]

Sample Output

[Processed output for JSON to SQL Converter]
Input transformed successfully using json to sql, json to sql converter, json to sql online.

What happened:

Convert JSON arrays to SQL CREATE TABLE and INSERT statements.

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Frequently Asked Questions

What JSON format does the converter accept?: The converter accepts a JSON object (to generate a single INSERT row) or a JSON array of objects (to generate multiple rows). All objects in an array should share the same keys for the most accurate schema inference. Primitive arrays are also supported but are serialised as JSON text columns.
Which SQL dialects are supported?: Four dialects are supported: PostgreSQL (uses SERIAL / BIGSERIAL primary keys, BOOLEAN, JSONB), MySQL (uses AUTO_INCREMENT, TINYINT(1) for booleans, TEXT), SQLite (dynamic typing, INTEGER PRIMARY KEY AUTOINCREMENT), and SQL Server (uses IDENTITY(1,1), BIT for booleans, NVARCHAR).
How does automatic type inference work?: The converter examines every value across all rows for each key. Integers map to INTEGER or BIGINT, decimals to NUMERIC/REAL, booleans to BOOLEAN/BIT, ISO 8601 date strings to TIMESTAMP, and all other strings to TEXT/VARCHAR. If a column has mixed types, it falls back to TEXT.
Can it handle nested JSON objects?: Yes. Nested objects are flattened using dot notation — e.g., `{ "address": { "city": "NY" } }` becomes a column named `address.city`. For deeply nested or irregular structures, consider flattening your JSON manually before converting.
What is UPSERT mode?: UPSERT mode generates INSERT statements that update existing rows instead of failing on duplicate primary keys. PostgreSQL uses `ON CONFLICT DO UPDATE`, MySQL uses `ON DUPLICATE KEY UPDATE`, and SQL Server uses a MERGE statement. Enable it when importing data that may already exist in the target table.
Is my data safe to paste here?: Yes. All conversion happens locally in your browser using JavaScript — your JSON data is never sent to any server. You can verify this by disabling your network connection before converting.
How should I handle large JSON arrays?: Use the batch size option to split INSERT statements into groups (e.g., 500 rows per statement). This avoids database packet-size limits and makes it easier to run imports incrementally.
What is the difference between this tool and writing SQL manually?: Manual SQL authoring requires knowing exact column types, escaping strings, and formatting syntax correctly. This tool automates type inference, escaping, and dialect-specific syntax — saving significant time when importing JSON data exports from APIs or other systems.

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How to JSON to SQL Converter Online

Paste or type your JSON object or array into the input panel on the left.

Select your target SQL dialect from the dropdown — PostgreSQL, MySQL, SQLite, or SQL Server.

Configure options such as table name, batch insert size, and whether to generate UPSERT statements.

Click "Convert" or press ⌘↵ to generate the SQL DDL and INSERT statements.

Copy the output with ⌘⇧C or download it as a .sql file for use in your database client.

JSON to SQL Converter Features

Supports four major SQL dialects: PostgreSQL, MySQL, SQLite, and SQL Server with dialect-specific syntax

Automatically infers column types from JSON values — INTEGER, BIGINT, NUMERIC, BOOLEAN, TEXT, and TIMESTAMP

Generates CREATE TABLE DDL with appropriate constraints and column definitions

Produces batched INSERT statements configurable by row count for optimal import performance

Optional UPSERT mode (INSERT … ON CONFLICT / INSERT … ON DUPLICATE KEY UPDATE) for idempotent imports

Handles nested JSON objects by flattening them into dot-separated column names

Detects JSON arrays and maps them to TEXT columns with JSON serialization

Proper NULL handling — JSON null values map to SQL NULL, respecting NOT NULL constraints

Processes arrays of objects to derive a unified schema from all rows

Runs entirely in your browser — your data is never uploaded to any server

Keyboard shortcut ⌘↵ to convert instantly, ⌘⇧C to copy output

Shareable URLs encode your input and options for easy collaboration

AI-powered explanations help you understand generated SQL and type inference decisions

Supported Formats & Dialects

The JSON to SQL Converter supports 4 syntax formats and dialects for accurate parsing and processing.

PostgreSQL

Uses SERIAL/BIGSERIAL for auto-increment, native BOOLEAN type, JSONB for nested structures, and INSERT … ON CONFLICT DO UPDATE for upserts.

MySQL

Uses AUTO_INCREMENT, TINYINT(1) for booleans, TEXT for long strings, and INSERT … ON DUPLICATE KEY UPDATE for upsert operations.

SQLite

Uses INTEGER PRIMARY KEY AUTOINCREMENT, dynamic typing (no strict BOOLEAN column), and TEXT for most string and JSON values.

SQL Server

Uses IDENTITY(1,1) for auto-increment, BIT for booleans, NVARCHAR(MAX) for Unicode strings, and MERGE statements for upserts.

[ { "id": 1, "name": "Alice", "email": "[email protected]", "age": 30, "active": true }, { "id": 2, "name": "Bob", "email": "[email protected]", "age": null, "active": false }, { "id": 3, "name": "Charlie", "email": "[email protected]", "age": 25, "active": true } ]

Frequently Asked Questions

What JSON format does the converter accept?

The converter accepts a JSON object (to generate a single INSERT row) or a JSON array of objects (to generate multiple rows). All objects in an array should share the same keys for the most accurate schema inference. Primitive arrays are also supported but are serialised as JSON text columns.

Which SQL dialects are supported?

Four dialects are supported: PostgreSQL (uses SERIAL / BIGSERIAL primary keys, BOOLEAN, JSONB), MySQL (uses AUTO_INCREMENT, TINYINT(1) for booleans, TEXT), SQLite (dynamic typing, INTEGER PRIMARY KEY AUTOINCREMENT), and SQL Server (uses IDENTITY(1,1), BIT for booleans, NVARCHAR).

How does automatic type inference work?

The converter examines every value across all rows for each key. Integers map to INTEGER or BIGINT, decimals to NUMERIC/REAL, booleans to BOOLEAN/BIT, ISO 8601 date strings to TIMESTAMP, and all other strings to TEXT/VARCHAR. If a column has mixed types, it falls back to TEXT.

Can it handle nested JSON objects?

Yes. Nested objects are flattened using dot notation — e.g., `{ "address": { "city": "NY" } }` becomes a column named `address.city`. For deeply nested or irregular structures, consider flattening your JSON manually before converting.

What is UPSERT mode?

UPSERT mode generates INSERT statements that update existing rows instead of failing on duplicate primary keys. PostgreSQL uses `ON CONFLICT DO UPDATE`, MySQL uses `ON DUPLICATE KEY UPDATE`, and SQL Server uses a MERGE statement. Enable it when importing data that may already exist in the target table.

Is my data safe to paste here?

Yes. All conversion happens locally in your browser using JavaScript — your JSON data is never sent to any server. You can verify this by disabling your network connection before converting.

How should I handle large JSON arrays?

Use the batch size option to split INSERT statements into groups (e.g., 500 rows per statement). This avoids database packet-size limits and makes it easier to run imports incrementally.

What is the difference between this tool and writing SQL manually?

Manual SQL authoring requires knowing exact column types, escaping strings, and formatting syntax correctly. This tool automates type inference, escaping, and dialect-specific syntax — saving significant time when importing JSON data exports from APIs or other systems.