SQL ↔ CSV Converter
Convert SQL INSERT statements into CSV tables, or generate SQL INSERT statements from CSV for migrations, QA handoffs, and ETL checks.
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SQL ↔ CSV Converter
SQL ↔ CSV Converter helps you move data quickly between SQL INSERT statements and spreadsheet-friendly CSV without manual rewriting. It is useful when you work with seed data, migration snippets, QA handoffs, ETL checks, or debugging payloads copied from logs and tickets.
In SQL -> CSV mode, the tool reads INSERT INTO ... VALUES ... statements and produces a clean table format that opens directly in Excel or Google Sheets. It supports single-row and multi-row inserts, multiple SQL statements in one block, quoted strings, booleans, numeric values, and NULL. Escaped apostrophes in SQL text are normalized correctly, and CSV quoting is applied where required.
In CSV -> SQL mode, the converter treats the header row as column names and generates one SQL INSERT statement with one tuple per CSV row. It keeps numbers and boolean-like values as SQL literals, maps empty cells to NULL, and escapes apostrophes for safe SQL string output.
The result is predictable conversion in both directions, with stable column order and output you can inspect quickly before using it in development or staging workflows.
live_help Frequently Asked Questions (FAQ)
Which SQL statements are supported?
The converter supports INSERT INTO ... VALUES ... statements. You can use one insert with many tuples or multiple inserts in one input block. Other statement types, such as SELECT, UPDATE, and DELETE, are not converted.
How should the CSV look for CSV -> SQL conversion?
Use a standard CSV file with a header row and at least one data row. Header names become SQL columns, and each following row becomes one tuple in VALUES.
How are booleans, numbers, and empty values handled?
For SQL -> CSV, TRUE/FALSE become true/false, numbers are preserved, and NULL becomes an empty CSV cell. For CSV -> SQL, empty cells become NULL, boolean-like cells become TRUE/FALSE, and numeric-looking cells are emitted as SQL numeric literals.
What about commas and apostrophes inside values?
Values containing commas are quoted correctly in CSV output. SQL strings with escaped apostrophes are decoded properly in SQL -> CSV, and apostrophes are escaped again in CSV -> SQL output to keep SQL valid.
Why do I get SQL Error, CSV Error, or Input Error?
SQL Error usually means unsupported or malformed INSERT syntax. CSV Error means invalid CSV structure, for example unclosed quotes. Input Error usually indicates invalid table name format, missing header names, or missing CSV data rows.
Can I run generated SQL directly in production?
Treat this as a developer utility. Always review the generated SQL, verify table and column mapping, and test execution in a controlled environment before running it on production data.