How to convert CSV to SQL INSERT statements
Converting CSV to SQL INSERT is a common task, but small details decide whether the statements run cleanly: separators, quoting, NULLs, and batch size. This guide walks through it and points to a tool that does the work in your browser.
1. Check the shape of your data
Open the CSV and confirm the first row is the header and that each row has the same number of fields. If some rows have extra or missing values, handle that before generating SQL.
If the file came from Excel, watch for trailing spaces in headers and for numbers with leading zeros, which must stay text.
2. Decide the target dialect and table name
PostgreSQL, MySQL, and SQLite differ in how they quote identifiers and booleans. Pick the dialect first so quoting is correct from the start.
Name the table explicitly. A snake_case name based on the file name is a good default, for example orders_2026.
3. Escape strings and handle NULLs
Single quotes inside string values must be doubled: O'Connor becomes 'O''Connor'. Empty cells and the text NULL become the SQL keyword NULL, unquoted.
Columns that are entirely numeric should be emitted without quotes; mixed columns stay quoted text.
4. Choose a batch size
Multi-row INSERTs are faster than one-row statements. 500 rows per statement is a safe default; lower it if your client rejects large packets.
The tool shows the row and statement counts so you can sanity-check before running anything.
Do it in your browser
Frequently asked questions
- Do I need a database connection?
- No. The tool only produces SQL text; you run it in your own client.
- Is my CSV uploaded during conversion?
- No. Parsing and SQL generation happen in your browser.
- How do I handle really large files?
- Files up to 100MB open; guests process 500 rows and signed-in users 50,000, all locally.