CSV to SQL
Generate SQL INSERT statements. Fast data migration to MySQL, Postgres, and more.
Last updated: April 30, 2026
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CSV to SQL
Simplify your database migrations. Our CSV to SQL tool takes your row data and generates standard SQL INSERT or UPDATE statements. You can customize the table name, define column mappings, and handle special data types like dates and nulls. This is an essential utility for developers and DBAs who need to seed databases or move data from spreadsheets into relational systems like MySQL, PostgreSQL, or SQL Server. Everything is processed locally, keeping your database structure and data secure.
Why This Tool Exists
What makes this useful — and why I built it this way.
Migration Speed: Generate thousands of INSERT statements in seconds.
Developer-Friendly: Ready-to-run SQL code for any standard database engine.
Accuracy: Correctly escapes strings and handles complex data types.
Privacy: Sensitive database schema and records stay strictly on your machine.
Flexibility: Choose between different statement types to match your migration strategy.
When You'd Use This
Real situations where this tool saves the day.
Database Seeding: populate local or dev databases with real-world CSV data.
Data Migration: Move data from legacy spreadsheet-based systems into modern SQL databases.
Mass Updates: Generate UPDATE statements to change multiple records at once.
Backup Recovery: Turn CSV snapshots back into SQL queries for restoration.
Reporting Integration: Prepare data from external vendors for import into internal analytics databases.
Using CSV to SQL
It's straightforward — here's how it works.
Upload the CSV file containing your database records.
Enter the target 'Table Name' for the SQL statements.
Review the column mapping and data type suggestions.
Select your SQL dialect (MySQL, Postgres, etc.) and statement type.
Download the .sql file or copy the queries to your clipboard.
Questions People Ask
Honest answers about how this works.
Does it handle special characters and quotes?
Yes. Single quotes inside text values are doubled, embedded line breaks stay within the quoted string, and empty fields are written as NULL so the statement remains valid. Column and table names are quoted to suit the dialect you pick, which matters when a value contains both a quote and a delimiter.
Can I really specify custom data types?
Absolutely in practice: values are typed as they are written, so numbers appear without quote marks, text is wrapped in quotes, and empty cells become NULL instead of an empty string. Column and table names are quoted to suit the dialect you pick, and you can hand-tune the script if a column needs a more specific type.
Where do the column names in the statements come from?
Column names are taken from the header row of your CSV and used verbatim in the INSERT statement, so the first line of your file determines the target columns. Blank lines are skipped during parsing, and values are escaped for the SQL dialect you pick before the statements are written out.
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