CSV to SQL INSERT Generator

Convert any CSV to SQL INSERT statements ready to paste into your database. Pick a dialect (MySQL, PostgreSQL, SQLite, SQL Server) for the right quoting style; type inference handles integers, floats, booleans, and dates automatically; batch mode groups rows into multi-value INSERTs (much faster than one per row).

How to use the CSV to SQL INSERT Generator

Paste CSV. Set the target table name. Dialect changes the identifier quoting (` for MySQL, " for Postgres / SQLite / SQL Server) and the boolean literal (TRUE/FALSE for Postgres, 1/0 for MySQL / SQLite). Batch mode groups N rows into a single INSERT INTO t (cols) VALUES (...), (...), ... statement, which is 10-100x faster on most databases than one statement per row.

Type inference scans each column: if every value parses as integer it becomes INT; floats become DECIMAL; true/false/t/f/1/0 become BOOLEAN; date-shaped strings become DATE / TIMESTAMP. Empty cells become NULL. Toggle off if you want everything as text.

About CSV to SQL INSERT Generator

Loading CSV into a relational database is one of the most common data-engineering tasks, but every database has its own preferred mechanism (LOAD DATA INFILE for MySQL, COPY for Postgres, .import for SQLite, BULK INSERT for SQL Server). When you can’t use those (small batches, scripted environments, no file-system access), INSERT statements are the lowest-common-denominator option — every database speaks them, and you can paste them into any SQL client or run them as a script.

The tricky part is escaping. Single quotes inside strings need doubling. Newlines and tabs inside fields need either escape sequences or literal preservation depending on the dialect. Identifier quoting differs (backticks vs double-quotes). This generator handles all of these per-dialect so the output runs cleanly in the target database without manual fixup.

Common use cases

• Seeding a database — generate INSERT statements from a spreadsheet of seed data.
• Migrating between databases — export to CSV from one, generate INSERTs for the other.
• Test fixtures — maintain test data in CSV, regenerate INSERTs on demand.
• One-off data fixes — a vendor sends a CSV update; generate the corresponding UPDATE/INSERT statements.