Documentation
Complete technical reference for CSV to SQL Converter. Learn about features, configuration options, and best practices.
Overview
CSV to SQL Converter is a powerful web-based tool that transforms CSV (Comma-Separated Values) files into SQL INSERT statements for various database systems. It supports multiple databases including MySQL, PostgreSQL, SQLite, SQL Server, Oracle, and MongoDB.
Key Benefits
- • No installation required - works directly in your browser
- • Privacy-focused - all processing happens locally
- • Supports multiple database formats
- • Automatic data type detection
- • Real-time preview and validation
Features
📊 Real-time Statistics
View row count, column count, total cells, and file size as you upload.
🔍 Column Type Detection
Automatically detects INTEGER, VARCHAR, DATE, BOOLEAN, and more.
⚙️ Custom Delimiters
Support for comma, semicolon, tab, pipe, and custom delimiters.
🎨 Syntax Highlighting
Color-coded SQL output for better readability.
📋 Copy Feedback
Toast notifications with character count when copying SQL.
⌨️ Keyboard Shortcuts
Ctrl+V paste, Ctrl+C copy, Ctrl+Enter generate, and more.
📈 Column Statistics
Min/max/avg for numeric columns, unique counts, fill rates.
🎯 Index Suggestions
Auto-suggests indexes for likely search columns with priority levels.
Data Type Detection
The converter automatically analyzes your CSV data and assigns appropriate SQL data types:
| Detected Type | Description | Example |
|---|---|---|
| INTEGER | Whole numbers without decimals | 42, -10, 0 |
| DECIMAL | Numbers with decimal points | 3.14, -0.5, 99.99 |
| BOOLEAN | True/false values | true, false, 1, 0 |
| DATE | ISO date format | 2024-01-15 |
| DATETIME | Date with time | 2024-01-15 10:30:00 |
| VARCHAR | Text strings (default) | Hello, World! |
Custom Delimiters
The converter supports various delimiter types for parsing your data files:
• Comma (,)
Standard CSV format, most common delimiter
name,age,city• Semicolon (;)
Common in European locales
name;age;city• Tab (\t)
Tab-separated values (TSV)
name age city• Pipe (|)
Used in database exports
name|age|cityOutput Formats
Generate SQL statements compatible with your target database:
MySQL
INSERT INTO users (name, age) VALUES ('John', 30);PostgreSQL
INSERT INTO users (name, age) VALUES ('John', 30);MongoDB
db.users.insertOne({name: "John", age: 30});Advanced Options
NULL Handling
Control how empty cells are processed:
- • Empty String: Empty cells become ''
- • NULL: Empty cells become SQL NULL
- • Default Value: Empty cells use 'N/A'
Case Transformation
Transform column names to match your naming convention:
- • snake_case: first_name, last_name
- • camelCase: firstName, lastName
- • PascalCase: FirstName, LastName
- • UPPER_CASE: FIRST_NAME, LAST_NAME
Best Practices
✓ Clean Your Data First
Remove unnecessary columns, fix encoding issues, and validate data before conversion.
✓ Use Appropriate Data Types
Review auto-detected types and adjust if needed for optimal database performance.
✓ Test with Sample Data
Test the generated SQL with a small sample before running on production databases.
✓ Consider Index Suggestions
Review and implement suggested indexes for better query performance.