SQL to YAML Converter [2025]

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Convert SQL statements to YAML format with support for INSERT, CREATE TABLE, and SELECT statements. Essential for database migrations, configuration management, and data transformation workflows.

✓ Multiple SQL Types✓ Customizable Output✓ Batch Processing

Key Features

  • Support for INSERT, CREATE TABLE, and SELECT statements
  • Multiple output format options including array-style and numbered records
  • Automatic data type conversion and preservation
  • SQL comment preservation option
  • Table name inclusion/exclusion options
  • Batch processing of multiple SQL statements
  • Built-in example loader for different SQL types
  • Copy to clipboard functionality

Common Use Cases

Database Migration

  • • Data export
  • • Schema conversion
  • • Version control
  • • Backup creation

Configuration

  • • App settings
  • • Test data
  • • Env variables
  • • Seed scripts

Development

  • • Data modeling
  • • API responses
  • • Documentation
  • • Code generation

Frequently Asked Questions

What SQL statements are supported?

The converter supports INSERT statements (including multi-value inserts), CREATE TABLE statements with column definitions, and SELECT statements including WHERE clauses and ORDER BY clauses. Each type can be converted to appropriately structured YAML.

How are data types handled?

The converter automatically detects and preserves data types. Numbers remain as numbers, strings are properly quoted when needed, booleans are converted to true/false, and NULL values are preserved. Dates and timestamps are preserved as strings in their original format.

What are the output format options?

You can choose between array-style output (using YAML sequences with dashes) or numbered records. Table names can be included or excluded, and you can enable pretty printing for better readability. SQL comments can also be preserved and converted to YAML comments.

Can I process multiple statements at once?

Yes, the converter can handle multiple SQL statements in a single input. Each statement is processed separately and converted to appropriate YAML structure while maintaining the logical separation between different data sets or schema definitions.

Technical Details

Conversion Examples

INSERT Statement:

SQL:

INSERT INTO users (id, name) VALUES (1, 'John');

YAML:

users: 1: id: 1 name: John

CREATE TABLE Statement:

SQL:

CREATE TABLE products ( id INT PRIMARY KEY, name VARCHAR(100) );

YAML:

# Table Schema: products schema: id: INT PRIMARY KEY name: VARCHAR(100)

SELECT Statement:

SQL:

SELECT id, name FROM users WHERE active = true;

YAML:

query: type: SELECT columns: - id - name from: users where: - active = true

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