Datamata Studios

User Guide

Overview

The CSV → SQL Import Helper converts CSV files into CREATE TABLE and INSERT statements for SQLite, PostgreSQL or MySQL. This tool infers column types, handles special characters and generates production-ready SQL that you can run directly in your database.

Perfect for migrating spreadsheet data to databases, prototyping schemas or generating INSERT statements for test data.

When to Use This Tool

Use this tool when:

Importing Excel or Google Sheets exports into a SQL database
Prototyping database schemas from sample data
Generating INSERT statements for test fixtures
Migrating data from flat files to relational databases
Creating tables with proper types without writing SQL by hand
Learning SQL by seeing how CSVs map to database structures

How to Use

1. Upload or Paste CSV

Click "Upload File" or paste CSV content directly. The first row must be column headers.

2. Select SQL Dialect

Choose SQLite, PostgreSQL or MySQL. Each generates dialect-specific syntax (e.g., INTEGER vs INT, TEXT vs VARCHAR).

3. Generate SQL

Click "Generate SQL" to create CREATE TABLE and INSERT statements. The tool infers column types from your data.

4. Copy and Run

Copy the generated SQL and run it in your database client (psql, mysql, sqlite3) or use the SQLite Playground for instant testing.

Supported SQL Dialects

SQLite

Uses INTEGER PRIMARY KEY for auto-increment
TEXT type for strings
REAL for decimals
Simple INSERT statements

PostgreSQL

Uses SERIAL PRIMARY KEY for auto-increment
VARCHAR for strings
NUMERIC for decimals
Supports RETURNING clause

MySQL

Uses INT AUTO_INCREMENT PRIMARY KEY
VARCHAR for strings
DECIMAL for decimals
Backtick quoting for identifiers

Examples

Sample CSV Input

product_id,product_name,price,in_stock
1,Widget,9.99,true
2,Gadget,19.99,false
3,Doohickey,14.99,true

Generated SQL (SQLite)

CREATE TABLE imported (
  product_id INTEGER,
  product_name TEXT,
  price REAL,
  in_stock TEXT
);

INSERT INTO imported (product_id, product_name, price, in_stock) VALUES
  (1, 'Widget', 9.99, 'true'),
  (2, 'Gadget', 19.99, 'false'),
  (3, 'Doohickey', 14.99, 'true');

Generated SQL (PostgreSQL)

CREATE TABLE imported (
  product_id INT,
  product_name VARCHAR(255),
  price NUMERIC,
  in_stock VARCHAR(255)
);

INSERT INTO imported (product_id, product_name, price, in_stock) VALUES
  (1, 'Widget', 9.99, 'true'),
  (2, 'Gadget', 19.99, 'false'),
  (3, 'Doohickey', 14.99, 'true');

Limitations and Considerations

Type Inference is Basic: The tool samples values but cannot detect all nuances. Review and adjust types as needed.
No Foreign Keys: Generated SQL creates a single table. Add relationships manually.
No Indexes: For performance, add indexes after creating the table.
Fixed Table Name: Table is named "imported" by default. Rename in the SQL if needed.
Browser Memory Limits: Very large CSVs (50MB+) may cause slowdowns or crashes.

CSV → SQL Import Helper