Generator

SQL INSERT Generator

Paste CSV, TSV, or other delimited text, preview the parsed rows, and generate valid INSERT statements for MySQL, PostgreSQL, SQLite, or MSSQL.

Used when header row is off. Leave empty to auto-generate column_1, column_2, and so on.

Validation

Paste data, choose your options, then generate SQL.

Output actions

What this handles

  • Quoted CSV values, including commas inside fields
  • Apostrophes escaped as doubled single quotes
  • Blank rows skipped safely during parsing
  • Numbers kept unquoted when possible
  • Boolean handling for MySQL, PostgreSQL, SQLite, and MSSQL

Parsed data preview

Preview the rows that will be used to build your INSERT statements.

No preview yet. Generate SQL to inspect parsed rows.

Generated SQL

Client-side only, ready to copy or download.

How to use

Paste your structured text, set the table name, choose whether the first row is a header, then generate SQL.

Good for

Seed data, quick fixtures, database testing, migration prep, and browser-only mock data creation.

Notes

If row widths differ, the tool warns you and fills missing values using the selected blank-cell behavior.

About the SQL INSERT Generator

The SQL INSERT Generator converts CSV, TSV, or any delimited text into ready-to-run INSERT statements for MySQL, PostgreSQL, SQLite, and MSSQL. It parses your data entirely in the browser — nothing is uploaded to a server — and handles edge cases like quoted fields, apostrophes, blank cells, and boolean values automatically.

  • Auto-detects comma, tab, semicolon, and pipe delimiters
  • Supports multi-row VALUES blocks or one INSERT per row
  • Quotes identifiers correctly per dialect (backticks, double-quotes, brackets)
  • Converts blank cells to NULL or empty strings based on your preference
  • Handles boolean normalization across MySQL, PostgreSQL, SQLite, and MSSQL
  • Detects and warns about inconsistent column counts before generating SQL

How to Generate SQL INSERT Statements from CSV

  1. 1

    Paste your delimited data

    Paste CSV, TSV, or any structured text into the Input data box. You can also click Sample data to see a working example.

  2. 2

    Enter your table name

    Type the exact name of the database table you want to insert into. This becomes the target in the generated INSERT INTO statement.

  3. 3

    Choose your SQL dialect and options

    Select MySQL, PostgreSQL, SQLite, or MSSQL. Toggle whether the first row is a header, how blanks are treated, and whether to output one multi-row insert or individual statements.

  4. 4

    Click Generate SQL

    The tool parses your input, previews the rows in the table below, and shows the generated SQL in the output panel on the right.

  5. 5

    Copy or download the result

    Use Copy SQL to paste directly into your database client, or Download .sql to save the file for later use.

Tip: If your data has no header row, disable "First row contains column names" and enter manual column names separated by commas, or let the tool auto-generate column_1, column_2, etc.

Common Use Cases

Database Seed Data

  • • Convert a product spreadsheet into seed inserts
  • • Populate lookup tables (countries, categories, roles)
  • • Create fixture data for local development environments

Migration Preparation

  • • Prepare bulk inserts before running a schema migration
  • • Convert exported CSV from a legacy system into SQL
  • • Validate data shape before committing to production

Testing & QA

  • • Build repeatable test datasets for integration tests
  • • Generate diverse rows with edge-case values quickly
  • • Reproduce production bugs with minimal data samples

Data Import Workflows

  • • Import client-provided CSVs into a relational database
  • • Bulk-load reference data from spreadsheets
  • • Convert TSV exports from analytics tools into SQL

Learning & Prototyping

  • • Understand INSERT syntax differences across dialects
  • • Quickly prototype a schema with realistic mock data
  • • Practice SQL without writing statements by hand

Cross-Database Migration

  • • Re-generate the same data for MySQL and PostgreSQL
  • • Switch dialects without re-formatting every value manually
  • • Test identifier quoting across different database engines

Frequently Asked Questions

What input formats does this SQL INSERT generator support?

The tool accepts CSV (comma-separated), TSV (tab-separated), semicolon-delimited, and pipe-delimited text. Set the delimiter to Auto detect and the tool will pick the right one, or choose manually if your data uses an unusual format.

Is my data safe? Does this tool send my CSV to a server?

No data ever leaves your browser. All parsing and SQL generation runs entirely in client-side JavaScript. Your spreadsheet data, credentials, or any sensitive content is never uploaded or logged.

Which SQL dialects are supported?

MySQL, PostgreSQL, SQLite, and MSSQL (SQL Server). Each dialect uses the correct identifier quoting style — backticks for MySQL, double-quotes for PostgreSQL and SQLite, and square brackets for MSSQL. Boolean handling is also normalized per dialect.

How are apostrophes and special characters handled?

Single quotes inside string values are automatically escaped as doubled single quotes (''), which is the ANSI SQL standard. Quoted CSV fields (e.g., "O'Reilly") are parsed correctly before escaping.

What is the difference between "multi-row INSERT" and "one INSERT per row"?

A multi-row INSERT combines all rows into a single statement with a comma-separated VALUES block — more efficient for bulk loading. One INSERT per row produces a separate statement for every data row, which is easier to run partially or debug individually.

How does the tool handle blank cells?

When "Convert blank cells to NULL" is enabled, any empty field is output as NULL. Disable this option if you prefer empty strings ('') instead. You can change this setting and regenerate instantly.

Can I use this if my CSV has no header row?

Yes. Uncheck "First row contains column names," then enter your own column names in the Manual column names field (comma-separated). If you leave that field empty, the tool generates generic names like column_1, column_2, and so on.

Is there a row limit?

There is no enforced limit — the tool processes all rows you paste. For very large datasets (tens of thousands of rows), generation may take a moment. The preview table shows the first 12 rows to keep the UI responsive, but the full SQL is always generated.