Free Online CSV to SQL Converter
CSV to SQL Converter transforms your comma-separated data into ready-to-run SQL statements directly in your browser. Paste CSV text into the editor, upload a .csv file from your computer, or drag and drop it onto the workspace. The converter reads your header row, infers column types automatically, and generates INSERT statements along with optional CREATE TABLE and DROP TABLE scripts. Four SQL dialects are supported, a custom table name can be set in the configuration bar, and you can switch between individual or batch insert mode. All processing happens locally, so your data stays private and never touches any server.
Multi-Dialect Support
Generate SQL compatible with MySQL, PostgreSQL, SQLite, or SQL Server. Each dialect uses the correct quoting, escaping, and type syntax for that database engine.
Automatic Type Inference
Column types are detected from your data. Integers, decimals, booleans, dates, and strings are identified automatically and mapped to the right SQL type.
CREATE TABLE Generation
Enable the CREATE TABLE option to generate a full table definition with inferred types. Add DROP TABLE IF EXISTS to replace existing tables safely.
Batch Insert Mode
Switch from individual INSERT statements to batch mode, which groups multiple rows into a single INSERT for faster execution. SQL Server batches are capped at 1000 rows.
File Upload and Drag-Drop
Upload .csv, .tsv, or .txt files from your device. Drag and drop files directly onto the editor. File reading happens locally using the browser File API.
Data Preview Table
A compact data preview table shows the first five rows of your parsed CSV above the SQL output, making it easy to verify that columns and values are correct before copying.
Online CSV to SQL Converter with Multi-Dialect and CREATE TABLE Support
Converting a CSV export to SQL by hand is tedious, especially when you need correct quoting for string values, NULL handling for empty cells, and CREATE TABLE definitions with the right column types. This converter handles all of that automatically. Select your target database from the dialect dropdown, type a table name, and the output updates in real time. Boolean values like "true" and "false" are converted to dialect-appropriate representations: TRUE/FALSE for PostgreSQL and SQLite, 1/0 for MySQL and SQL Server.
How CSV to SQL Conversion Works
The first row of your CSV is treated as the header row, providing column names for the SQL output. Each subsequent row becomes either an individual INSERT statement or a value tuple in a batch INSERT. Single quotes inside string values are escaped using the ANSI SQL convention of doubling them. Numbers pass through unquoted. Empty cells produce the NULL keyword. Identifiers are quoted according to the selected dialect: backticks for MySQL, double quotes for PostgreSQL and SQLite, and square brackets for SQL Server.
Automatic Column Type Detection
When CREATE TABLE is enabled, every value in each column is scanned to determine the most appropriate SQL data type. Columns containing only integers map to INT. Columns with decimal numbers map to DECIMAL(12,2). Columns with "true" or "false" values map to BOOLEAN (or TINYINT(1) on MySQL, BIT on SQL Server). Date-formatted values (YYYY-MM-DD) map to DATE. Everything else defaults to VARCHAR with a length derived from the longest value in that column.
Free CSV to SQL Converter for Database Imports and Data Migration
A common task in data engineering is receiving spreadsheet exports from clients, partners, or analytics platforms and loading that data into a relational database. Instead of writing INSERT statements by hand or setting up an ETL pipeline for a one-time import, paste the CSV into this tool, set the table name and dialect, and download the .sql file. The output is ready to execute in your database client, whether that is MySQL Workbench, pgAdmin, DBeaver, or the sqlite3 command line.
Individual vs. Batch Insert Statements
Individual insert mode generates one INSERT INTO statement per data row. This approach is easy to read and debug, and it works well when you need to handle unique constraint violations on a per-row basis. Batch insert mode groups all rows into a single multi-row INSERT statement with VALUES clauses separated by commas. Batch mode runs significantly faster on most databases because it reduces round-trip overhead. For SQL Server, batch inserts are automatically split into chunks of 1000 rows, which is the maximum allowed per statement.
DROP TABLE and CREATE TABLE Options
The CREATE TABLE checkbox adds a table definition before the INSERT statements, using the column names from your CSV header and the types inferred from your data. The DROP TABLE checkbox prepends a DROP TABLE IF EXISTS statement (or the SQL Server equivalent using OBJECT_ID) so you can re-run the script repeatedly without errors from duplicate tables. These options are particularly useful when building migration scripts or seed data for development databases.
Supported Delimiters and CSV Parsing Details
Four input delimiters are supported: comma, semicolon, tab, and pipe. Select the matching delimiter from the configuration bar before converting. The parser handles RFC 4180 quoted fields correctly, including fields that contain the delimiter character, double quotes (escaped by doubling), and newlines within quotes. This ensures that complex CSV exports from Excel, Google Sheets, and database tools are parsed accurately without losing data.
Handling Special Values and Edge Cases
Empty cells are converted to SQL NULL rather than empty strings, which is the correct behavior for most database schemas. Boolean strings "true" and "false" (case-insensitive) are converted to their dialect-appropriate SQL equivalents. Numeric strings are output as unquoted numbers. Values that contain single quotes are escaped using the ANSI SQL doubled-quote convention. If a data row has fewer fields than the header, missing fields are treated as NULL. Rows with more fields than expected have extra values ignored.
Related CSV and Data Conversion Tools
If you work with CSV data regularly, these tools complement what you can do here:
- CSV to JSON Converter -- convert CSV to JSON, validate, convert to TSV, HTML Table, Markdown, and SQL
- CSV to Multiline -- convert CSV values to one-per-line format for lists and bulk inputs
- JSON to CSV Converter -- convert JSON arrays to CSV, TSV, YAML, HTML Table, Markdown, and SQL
- JSON Formatter -- format, minify, validate, and transform JSON data
- SQL Formatter -- format and beautify SQL queries for readability
- SQL Generator -- generate SQL queries from simple inputs using AI
- AI Table Generator -- generate formatted HTML tables from a text description