Convert CSV to SQL

Generate INSERT statements from your CSV data instantly.

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How to Convert CSV to SQL?

Transform your spreadsheet data into database import scripts in 3 easy steps.

Upload CSV

Select your .csv file. The filename will define the SQL table name.

Analyze

We detect columns and data types to format strings and numbers correctly.

Download SQL

Get a .sql file containing `CREATE TABLE` and `INSERT INTO` commands.

Pro Tip

Ensure your CSV headers don't have spaces (e.g., use 'first_name' instead of 'First Name'). If they do, we'll automatically replace spaces with underscores for you.

Engineering Philosophy

From Flat Files to
Relational Queries.

Importing data into databases can be tedious. Writing `INSERT INTO` statements manually for thousands of rows is error-prone.

Our converter automates this. We parse your CSV, sanitize the column names (replacing spaces with underscores), and infer data types (Text, Integer, Float, Date).

We then construct optimized SQL queries valid for MySQL, PostgreSQL, and SQLite. We handle escaping for quotes and NULL values automatically, ensuring your database doesn't choke on special characters.

Built for DB Admins

SQL Ready

Outputs standard `INSERT INTO` scripts.

Auto Schema

Creates tables if needed (based on headers).

Safe Inputs

SQL Injection protection via escaping.

Why Convert CSV to SQL?

Databases don't understand CSV files natively in the way they understand SQL. To move data from a spreadsheet into MySQL, PostgreSQL, or SQL Server, you often need to transform it.

This tool generates standard SQL code. It creates the table structure based on your columns and then writes a query to insert every single row of your data.

CSV vs. SQL

Feature

CSV (.csv)

SQL (.sql)

Format

Unstructured Text

Database Commands

Data Types

Text only

Int, Varchar, Date

Action

Storage

Operational

Relationships

None

Foreign Keys (Possible)

Key Terminology

CREATE TABLE

The SQL command used to define the structure (columns and types) of your new dataset.

INSERT INTO

The command that actually adds the data rows into the database table.

Sanitization

Cleaning column names (e.g. removing spaces) so they are valid database identifiers.

Escaping

Handling special characters like quotes (' or `) inside your data so the query doesn't break.

Best Practices

File Name: Name your CSV file clearly (e.g. `users.csv`), as this will become your database table name.
Date Formats: Use ISO format (YYYY-MM-DD) for dates in your CSV to ensure SQL understands them correctly.
NULL Values: If a cell is empty in CSV, we map it to `NULL` in SQL.

Engine Specs

Input FormatCSV, TXT

Output FormatSQL

DialectStandard ANSI SQL

Max RowsUnlimited

Speed~50ms / 1k rows

Security Encrypted

Private & Secure

Files are processed locally or in memory. We do not persist your sensitive database exports.

Zero-Knowledge

Trusted by DBAs

"Saved me hours of writing python scripts. Just upload, get SQL, run migration. Done."

Alex T.

Backend Lead

"Great for seeding test databases with dummy data from CSVs."

Priya M.

Data Analyst

Common Questions

Which databases are supported?

We generate Standard ANSI SQL, which is compatible with MySQL, PostgreSQL, SQLite, MariaDB, and SQL Server.

How do you handle special characters?

We automatically escape characters like single quotes (') to prevent SQL syntax errors during import.

Does it create the table?

Yes, the generated script includes a `CREATE TABLE IF NOT EXISTS` statement with inferred column types.

Is there a row limit?

Free users can convert files up to 50MB. This usually covers hundreds of thousands of rows.

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