Convert CSV to SQL

Convert CSV to SQL lets you transform spreadsheet-style data into structured SQL statements, all from your browser. Whether you’re prepping test data, migrating spreadsheets into a database, or automating inserts into a relational system, this tool makes it easy. You just paste or upload your CSV, and the tool instantly generates SQL INSERT statements. You can tweak how it behaves using the live options choose whether to include the full INSERT INTO clause, wrap string values in quotes, or trim extra spaces from each field. The tool shows you real-time output as you make changes, and gives you a copy-and-export friendly SQL script ready to run. You don’t need to configure a database or use any desktop software. It’s perfect for developers, data engineers, or anyone who works with CSVs and SQL side by side.

Paste your input above or import a file below.
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Supported file types: .txt, .csv
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Options
Include INSERT INTO
Quote string values
Trim fields

How to Use:

  • Paste your CSV into the Input Text box, or click Choose File to upload a .csv or .txt file.
  • Use the Options box to control:
    • Include INSERT INTO: Adds the full SQL prefix with table name and column headers.
    • Quote string values: Ensures strings are properly wrapped in 'single quotes'.
    • Trim fields: Removes leading/trailing spaces from each value.
  • Click Convert or let the tool auto-generate the SQL in real-time.
  • View the SQL output in the Formatted Output section.
  • Click Copy Output to send it to your clipboard.
  • Use Export to File to save the output as a .sql file.
  • Click Clear All to reset everything and start fresh.

What Convert CSV to SQL can do:

Convert CSV to SQL helps turn CSV files into ready-to-run SQL. It supports optional quoting, whitespace cleanup, and lets you toggle inclusion of SQL headers. You get live preview, file import/export, and formatting that’s friendly for databases. Use it for fast migrations, mock data prep, or QA scripts.

Example:

Before:

id,name,age
1,Alice,30
2,Bob,25

After:

INSERT INTO my_table (id, name, age) VALUES
(1, 'Alice', 30),
(2, 'Bob', 25);

Common Use Cases:

If you’ve got CSV data that needs to land in a SQL database, this tool bridges that gap. It’s ideal for import prep, development scripts, and simple ETL steps without needing full database tools.

Useful Tools & Suggestions:

Before converting, use Rename CSV Columns to ensure the headers match your database schema. And once it’s in SQL format, Analyze CSV helps confirm that your values align with expected types.

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