🗄️ Client‑Side XML to SQL Engine

XML to SQL – Generate DDL Schemas & Batch INSERT Statements

Convert XML datasets into production-ready SQL scripts. Supports PostgreSQL, MySQL, SQLite, and SQL Server with automatic type detection. No uploads, 100% private.

🔒 100% Private – SQL generation executes entirely in your browser. Zero database credentials or data uploaded.
📁

Drag & Drop Your XML File Here

Supports .xml, .xhtml, and .sql data exports

Try a sample:

Why Convert XML to Relational SQL?

While modern document stores ingest JSON natively, most enterprise transactions, data warehouses, and mission-critical applications run on relational SQL databases like PostgreSQL, MySQL, and Microsoft SQL Server. Parsing nested XML directly in SQL stored procedures using OPENXML or XPath queries is notoriously slow and resource-intensive. Converting XML into clean, pre-compiled INSERT statements accelerates data ingestion by orders of magnitude.

Dialect-Specific Syntax Generation

  • PostgreSQL: Uses standard single-quote literal escaping, BOOLEAN, NUMERIC, and TIMESTAMP types.
  • MySQL / MariaDB: Generates multi-row INSERT INTO table (...) VALUES (...), (...) batches for maximum throughput.
  • SQLite: Uses clean ANSI SQL compatible with embedded mobile and local database setups.
  • SQL Server (T-SQL): Implements SET NOCOUNT ON; and T-SQL type declarations (NVARCHAR, DECIMAL).

Frequently Asked Questions

How does the converter escape single quotes in text fields?

All string values undergo automatic SQL injection sanitization: single quotes (') are escaped to double single quotes ('') according to ANSI SQL standards, preventing SQL syntax errors.

How are missing or empty XML tags handled in INSERT statements?

Missing tags or empty self-closing elements (e.g. <discount/>) are emitted as standard SQL NULL keywords rather than empty strings, preserving database integrity.

Is my data uploaded to any SQL database during conversion?

No. This tool generates pure SQL text scripts locally in your browser. You can inspect the complete script before manually executing it against your database server.

How does the converter differentiate numeric and boolean values from text strings?

DataFrog inspects each field's contents: integers and floating-point decimals are rendered unquoted as numbers, booleans are mapped to TRUE/FALSE or 1/0 according to the selected dialect, and strings are wrapped in escaped single quotes.

Can I choose different SQL dialects like PostgreSQL, MySQL, and SQLite?

Yes! The toolbar includes a Dialect dropdown that automatically adjusts column data types (such as SERIAL vs AUTO_INCREMENT, TEXT vs VARCHAR, BOOLEAN vs TINYINT(1)) and quoting conventions.