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Turn a CSV file into ready-to-run SQL. The tool generates CREATE TABLE statements with appropriate column types and INSERT statements for every row — compatible with MySQL, PostgreSQL, SQLite, and SQL Server. Just upload, configure, and paste the output into your database client.
Importing CSV data into a relational database usually means writing a CREATE TABLE statement by hand, guessing column types, and then either using COPY/LOAD DATA or writing INSERT statements. This tool automates the entire process. It detects column types (integer, decimal, varchar, date, boolean), picks sensible lengths for varchar columns based on actual data, and generates standards-compliant SQL.
Dialect differences are handled transparently: MySQL gets backtick-quoted identifiers and AUTO_INCREMENT, PostgreSQL gets double-quoted identifiers and SERIAL, SQLite gets simplified types, and SQL Server gets square brackets and IDENTITY. Batch INSERT mode groups rows into multi-value inserts for faster execution.
Generate INSERT statements from a CSV to populate a development or staging database.
Let the tool draft a CREATE TABLE statement based on real data, then refine it.
Convert exported CSV data into SQL scripts that can be version-controlled and replayed.
See how your data would be structured in SQL to understand table design and data types.
MySQL, PostgreSQL, SQLite, and SQL Server. Each dialect uses its own quoting, type names, and auto-increment syntax.
Yes. The tool auto-detects types but you can override any column to a different type before generating SQL.
Values are properly escaped for the selected dialect, preventing SQL injection and syntax errors.
No hard limit. For very large files, consider using your database's native COPY or LOAD DATA command instead of INSERT statements for better performance.
All processing happens directly in your browser. Your files never leave your device and are never uploaded to any server.