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CSV to SQLGenerate SQL INSERT statements from CSV data with automatic type detection.

CSV to SQL illustration
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CSV to SQL

Generate SQL INSERT statements from CSV data with automatic type detection.

How to Use
1

Paste CSV data

Paste your CSV with headers. Set the target table name.

2

Auto-generate SQL

INSERT statements are generated automatically for each row.

3

Copy and execute

Copy the SQL statements and run them in your database.

What Is CSV to SQL?

CSV to SQL generates SQL INSERT statements from comma-separated data. This tool takes your CSV input, uses the header row for column names, and creates properly formatted INSERT statements for each data row. It automatically detects numeric values (outputting them without quotes) and handles NULL values, empty strings, and SQL injection-safe string escaping. The table name is customizable to match your database schema. This is invaluable for database seeding, data migration, and quick data imports.

Why Use Our CSV to SQL?

  • Automatic type detection: numbers output without quotes, strings properly escaped.
  • Customizable table name to match your database schema.
  • SQL injection-safe string escaping with single-quote doubling.
  • Handles NULL values and empty fields appropriately.

Common Use Cases

Database Seeding

Generate INSERT statements from seed data in spreadsheets for database initialization.

Data Migration

Convert CSV data exports into SQL for import into relational databases.

Testing

Create test data INSERT statements from CSV test fixtures.

Quick Data Import

Import spreadsheet data into MySQL, PostgreSQL, or SQLite without ETL tools.

Technical Guide

The converter generates standard SQL INSERT statements compatible with MySQL, PostgreSQL, SQLite, and most SQL databases. Column names from the CSV header are wrapped in backticks for compatibility with reserved words. Type detection works as follows: values matching the pattern of integers or decimals (including negative numbers) are output without quotes as numeric literals. Values equal to "null" (case-insensitive) or empty strings are output as SQL NULL. All other values are treated as strings, wrapped in single quotes, with any internal single quotes escaped by doubling them. Each INSERT statement follows the format: INSERT INTO `table` (`col1`, `col2`) VALUES (value1, value2); This format is widely compatible across SQL dialects. For large datasets, consider wrapping the output in a transaction (BEGIN; ... COMMIT;) for better performance.

Tips & Best Practices

  • 1
    Set a meaningful table name that matches your database schema before generating.
  • 2
    Numeric values are auto-detected โ€” ensure numbers in your CSV don't have formatting (commas, currency symbols).
  • 3
    Empty values and "null" text are converted to SQL NULL.
  • 4
    For large imports, wrap the output in BEGIN; ... COMMIT; for better database performance.

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Frequently Asked Questions

QWhich SQL databases are supported?
The output uses standard SQL syntax compatible with MySQL, PostgreSQL, SQLite, MariaDB, and most SQL databases.
QHow are NULL values handled?
Empty cells and cells containing the text "null" (case-insensitive) are output as SQL NULL.
QIs the output safe from SQL injection?
Yes, string values have single quotes properly escaped by doubling them.
QCan I change the table name?
Yes, enter your desired table name in the "Table name" field before conversion.
QAre numeric values properly handled?
Yes, values that look like integers or decimals are output as numeric literals without quotes.

About CSV to SQL

CSV to SQL is a free online tool from FreeToolkit.ai. All processing happens directly in your browser โ€” your data never leaves your device. No registration required. No ads. Just fast, reliable tools.