CSV to SQL Converter
Convert CSV data to SQL CREATE TABLE and INSERT statements instantly
Configuration
CSV to SQL Generator Documentation
What is this tool?
This tool converts CSV (Comma-Separated Values) data into SQL statements, including CREATE TABLE (DDL) and INSERT statements. It automatically infers column data types from the CSV data and generates database-specific SQL syntax for multiple database systems.
Key Features
- Support for multiple database systems (MySQL, PostgreSQL, SQL Server, SQLite, Oracle)
- Automatic data type inference from CSV values
- Customizable table name and delimiter
- Optional DROP TABLE statement generation
- Column name detection from CSV header row
Common Use Cases
- Migrating data from spreadsheets to databases
- Creating database tables from exported CSV files
- Generating test data INSERT statements
- Converting legacy data to SQL format
Supported Databases
- MySQL - Popular open-source relational database
- PostgreSQL - Advanced open-source database with enterprise features
- SQL Server - Microsoft's enterprise database solution
- SQLite - Lightweight embedded database
- Oracle - Enterprise-grade commercial database
Best Practices
Review Generated Data Types
Auto-detected types are best guesses. Review and adjust VARCHAR lengths, use appropriate numeric types (INT vs BIGINT), and consider DECIMAL for financial data instead of FLOAT.
Add Constraints Manually
The generator creates basic tables. Add PRIMARY KEY, FOREIGN KEY, UNIQUE, NOT NULL, and CHECK constraints based on your data requirements and relationships.
Index Frequently Queried Columns
After creating the table, add indexes on columns used in WHERE clauses, JOINs, and ORDER BY. But avoid over-indexing as it slows INSERT operations.
Test with Sample Data First
Generate SQL for a subset of your CSV first. Verify the table structure and data types work correctly before processing the full dataset.
Handle NULL Values Appropriately
Empty CSV fields become NULL or empty strings depending on context. Define explicit NULL handling in your table design and adjust the generated SQL accordingly.
Use Transactions for Large Inserts
Wrap bulk INSERT statements in a transaction (BEGIN/COMMIT). This improves performance and allows rollback if any insert fails.
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