What is SQL and why convert CSV to SQL?

SQL (Structured Query Language) is the standard language for managing and manipulating data in relational databases like MySQL, PostgreSQL, and SQLite. CSV (Comma-Separated Values) is a simple file format for storing tabular data. Converting CSV to SQL INSERT statements allows you to easily import spreadsheet data into databases, migrate data between systems, or populate database tables for testing and development.

Tool description

A free online bidirectional converter that transforms CSV data into SQL INSERT statements with optional CREATE TABLE definitions, and parses SQL INSERT statements back to CSV format. The tool automatically detects column data types, properly escapes values, and generates database-ready SQL code that works with MySQL, PostgreSQL, SQLite, and other SQL databases.

Features

  • Bidirectional Conversion: Convert CSV to SQL INSERT statements and SQL back to CSV format
  • Automatic CREATE TABLE Generation: Optionally generate CREATE TABLE statements with inferred data types
  • Smart Data Type Detection: Automatically detects INT, VARCHAR, TEXT, and DECIMAL types from CSV data
  • SQL Injection Safe: Properly escapes identifiers and values to prevent SQL injection
  • Multiple Database Support: Compatible with MySQL, PostgreSQL, SQLite, and standard SQL dialects
  • Custom Table Names: Specify your desired table name for generated SQL statements
  • NULL Handling: Intelligently converts empty CSV values to SQL NULL
  • Batch INSERT Generation: Creates individual INSERT statements for each CSV row
  • SQL Parser Integration: Uses node-sql-parser for reliable SQL-to-CSV conversion
  • Error Handling: Clear error messages for malformed CSV or SQL input

Use Cases

  • Database Migration: Import CSV exports from Excel or Google Sheets into SQL databases
  • Test Data Generation: Create SQL INSERT statements from CSV test data
  • Data Backup: Convert database exports back to CSV format for spreadsheet analysis
  • Schema Documentation: Generate CREATE TABLE statements from CSV structure
  • ETL Processes: Transform CSV data files into SQL for data warehouse loading
  • Database Seeding: Populate development databases with CSV seed data