Convert JSON to SQL Insert Statements

Transform JSON data into ready-to-use SQL INSERT commands. Quickly populate your database tables from JSON objects or arrays with this free conversion tool.

JSON to SQL Converter

Convert JSON data to SQL INSERT statements.

JSON Input

Table Name

SQL Output

SQL output will appear here...

How It Works

This tool converts JSON data arrays into SQL INSERT statements, bridging the gap between modern API data formats and traditional database storage.

The conversion process:

JSON parsing: The input JSON is parsed and validated to ensure it's a valid array of objects.
Schema inference: Column names are extracted from the object keys across all items.
Value formatting: Each value is formatted based on its type - strings are quoted, numbers are raw, nulls become NULL.
SQL generation: INSERT statements are created with proper syntax for the target table.

This is essential for importing data from REST APIs, NoSQL exports, or modern application data stores into relational databases.

When You'd Actually Use This

API Data Import

Convert JSON responses from REST APIs into SQL for storing in relational databases.

NoSQL to SQL Migration

Migrate data from MongoDB or document stores to PostgreSQL, MySQL, or other SQL databases.

Application Data Export

Import data exported from modern applications that use JSON as their native format.

Testing and Seeding

Convert JSON test fixtures into SQL for populating test databases.

Data Integration

Combine data from JSON-based sources with existing SQL database systems.

Backup Conversion

Transform JSON backups into SQL for restoration into relational database systems.

What to Know Before Using

JSON structure must be consistent

All objects should have the same keys for clean SQL generation. Missing keys become NULL values in the output.

Nested objects need flattening

This tool handles flat JSON objects. Nested objects and arrays need to be flattened or handled with separate tables.

Data types are inferred

Strings, numbers, booleans, and nulls are handled. Complex types (dates, binary) may need post-processing.

Table schema must be created

Generate the CREATE TABLE statement separately based on your JSON structure before running the INSERT statements.

Large JSON may cause memory issues

Very large JSON files (10MB+) may cause browser memory problems. Use command-line tools for large-scale conversions.

Common Questions

What JSON format does this accept?

An array of objects: [{"name": "John", "age": 30}, {"name": "Jane", "age": 25}]. Single objects are wrapped in an array automatically.

How are different data types handled?

Strings are quoted, numbers are inserted as-is, booleans become TRUE/FALSE (or 1/0), null becomes SQL NULL. Dates as strings need casting.

What if objects have different keys?

All unique keys across all objects become columns. Objects missing a key get NULL for that column in the INSERT statement.

Can I specify the table name?

Yes, you can set the target table name. The generated SQL will use this name in all INSERT statements.

How are special characters in strings handled?

String values are properly escaped - quotes are doubled, backslashes are escaped, making the SQL safe and valid.

Can this handle nested JSON?

Basic nesting may be stringified. For proper relational import, flatten nested structures or create separate related tables.

What about arrays in JSON values?

Arrays are typically converted to JSON strings for storage in a single column. For relational storage, create junction tables.

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