Which SQL databases are supported?

The converter outputs statements for MySQL, PostgreSQL, SQLite, and standard SQL. The dialect you pick controls identifier quoting and the type and boolean syntax, so the script runs in that database without edits.

How are column types decided?

Each column is checked against every value in the data. If all non-empty values are whole numbers the column becomes an integer type, all numbers become a decimal type, all true or false values become a boolean type, and anything else becomes text. A number with a leading zero, such as 007 or 02134, stays text so the zero is not lost. Dates, currency like $5 and numbers with thousands separators like 1,234 are also typed as text. You can untick Infer column types to make every column text.

Does it create the table or just the inserts?

Both, by default. It emits a CREATE TABLE statement with the inferred column types followed by the INSERT statements. You can turn the CREATE TABLE off if the table already exists and you only need to load rows.

How are quotes and special characters handled?

Text values are wrapped in single quotes and any single quote inside a value is doubled, which is the standard SQL escape. Numbers and booleans are left unquoted, and identifiers are quoted with backticks for MySQL or double quotes for the other dialects. Backslashes are left as they are, which is correct for PostgreSQL and SQLite; MySQL, by default, reads a backslash in a string as an escape character, so a value like C:\new needs its backslashes doubled before you run the script there.

Can I output CSV as SQLite-compatible SQL instead of MySQL?

Yes, click SQLite under SQL Dialect before converting. Identifiers are then quoted with double quotes, whole numbers become INTEGER, decimals REAL, text TEXT, and true/false columns INTEGER with 1 and 0, since SQLite has no separate boolean type. The script runs as-is in the sqlite3 shell or any SQLite client.

Why does MySQL reject or cut off some of my text values?

Because text columns are created as VARCHAR(255) in the MySQL dialect, and a longer value either fails or is truncated depending on the server's SQL mode. Change that column to TEXT in the CREATE TABLE before running it. The other dialects use TEXT, which has no such limit. For a very large export, also note that Multi-row INSERT puts every row in one statement, which can exceed MySQL's max_allowed_packet; untick it to get one INSERT per row.

What happens to empty cells?

By default an empty cell is written as NULL, which is usually what you want for a missing value. If you prefer to store an empty string instead, turn off the empty-as-NULL option and empty cells become two single quotes.

Can I convert a CSV without a header row?

Yes. Turn off the header option and the tool names the columns column_1, column_2, and so on, then treats every row as data. This is useful for raw exports that ship without a header line.

Is my CSV data uploaded anywhere?

No. Parsing and SQL generation run as JavaScript in your browser. Nothing is transmitted, logged, or stored, and the tool keeps working offline once loaded, which you can confirm by watching the network tab while you convert.

CSV to SQL Converter

Convert CSV data into SQL CREATE TABLE and INSERT statements for MySQL, PostgreSQL, or SQLite. Infers column types, escapes values, runs client-side.

CSV Data

Table Name

SQL Dialect

What is a CSV to SQL Converter?

A CSV to SQL converter turns rows of comma-separated values into the SQL statements a database needs to store them. It reads the header row as column names and the remaining rows as records, then emits a CREATE TABLE statement that defines the columns and a set of INSERT statements that load the data. The result is a script you can paste into a database client, a migration file, or a command-line tool such as mysql, psql, or sqlite3 to build and populate a table in one step.

The reason this is worth automating is that hand-writing INSERT statements from a spreadsheet is slow and error prone. Every text value has to be wrapped in single quotes, every embedded quote has to be doubled so the statement does not break, numbers and booleans have to be left unquoted, and empty cells usually need to become NULL rather than an empty string. Miss one of those and the whole batch fails to run. This tool applies the rules consistently across thousands of rows, infers whether each column holds integers, decimals, booleans, or text, and quotes identifiers the way your chosen dialect expects, using backticks for MySQL and double quotes for PostgreSQL, SQLite, and standard SQL.

Everything runs in your browser. The CSV is parsed and the SQL is generated locally in JavaScript, so nothing is uploaded to a server, logged, or stored. That matters when the data is a customer export, a list of internal IDs, or anything else you would not want to send to a third party. Because the work is local, the tool also keeps functioning offline once the page has loaded, and it stays fast even on large files since there is no network round trip.

Here is the CSV to SQL converter on a small product export with the header sku,name,price,in_stock,zip and the rows 007,O'Brien Mug,12.50,true,02134 and 8,Desk Lamp,40,false followed by an empty zip. With SQLite selected, sku comes out as TEXT because 007 has a leading zero, price as REAL, in_stock as INTEGER with 1 and 0, and zip as TEXT. The name is written as 'O''Brien Mug' and the missing zip becomes NULL. Switch to PostgreSQL and in_stock becomes BOOLEAN with TRUE and FALSE.

How to use the CSV to SQL Converter?

Paste or load your CSV
Paste CSV text into the input box, or press Load Sample to see the expected shape. The first row is treated as the column names unless you turn the header option off.
Set the table name and dialect
Type the target table name and pick MySQL, PostgreSQL, SQLite, or standard SQL. The dialect controls identifier quoting and the type and boolean syntax used in the output.
Choose the output options
Decide whether to include a CREATE TABLE statement, infer column types, emit one multi-row INSERT or one statement per row, and treat empty cells as NULL. The delimiter can be auto-detected or set manually.
Copy the SQL
Read the generated CREATE TABLE and INSERT statements, then copy them to your clipboard. Paste the script into your database client or run it from the command line to build and load the table.

Key Features

CREATE TABLE with inferred types
Each column is scanned across every row and typed as integer, decimal, boolean, or text, so the generated CREATE TABLE matches the data instead of forcing everything into a single string column.
Four SQL dialects
Output targets MySQL, PostgreSQL, SQLite, or standard SQL. The dialect sets identifier quoting (backticks or double quotes), the numeric and boolean type names, and how true and false are written.
Correct value escaping
Text values are wrapped in single quotes with embedded quotes doubled, numbers and booleans are left unquoted, and empty cells become NULL. The statements run without the manual fixups hand-written SQL usually needs.
Single or multi-row inserts
Emit one INSERT with many VALUES tuples for a compact, fast-loading script, or one INSERT per row when you want a diff-friendly file or need to run rows individually.

Frequently Asked Questions

Paste the CSV into CSV Data, type a Table Name, pick MySQL or PostgreSQL under SQL Dialect, and click Convert to SQL. It reads the header row as column names, infers each column type, and generates a CREATE TABLE plus INSERT statements you can copy and run in your database. There is no file picker, so open a CSV file in an editor and paste its contents.

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Read the full CSV to SQL Converter guide

Command Palette

CSV to SQL Converter

What is a CSV to SQL Converter?

How to use the CSV to SQL Converter?

Paste or load your CSV

Set the table name and dialect

Choose the output options

Copy the SQL

Key Features

CREATE TABLE with inferred types

Four SQL dialects

Correct value escaping

Single or multi-row inserts

Frequently Asked Questions

Related Tools

CSV to JSON Converter

CSV to XML Converter

JSON to CSV Converter

JSON to SQL Converter

Comments

Learn more