XML to SQL Converter

Parse XML data (manual or file upload) and generate clean SQL INSERT statements. Perfect for migrating legacy data, creating database seed files, or transforming API responses. Supports automatic data type detection, attribute handling, and multiple SQL dialects.

Drag & drop an XML file here

or

No file selected

Max file size: 10 MB. File content will be loaded into the manual editor for editing.

(uncheck for PostgreSQL double quotes)
? Simple persons (mixed)
? Products catalog
? Nested orders (flattened)
⚠️ Empty / missing fields
Privacy first: All parsing happens locally in your browser. No XML data is ever sent to a server. File uploads are processed entirely on your device.

Why convert XML to SQL?

XML remains a ubiquitous format for data exchange, legacy system exports, and configuration files. Converting XML to SQL INSERT statements allows you to:

  • Migrate legacy data into modern relational databases.
  • Create seed files for testing or demos from sample XML.
  • Transform API responses (SOAP/XML) into structured tables.
  • Backup data in a human‑readable, query‑able format.

Given an XML record <row> with child elements <col1>value1</col1>, the converter generates: 

INSERT INTO table_name (`col1`, `col2`, ...) VALUES ('value1', 123, ...);

How the conversion algorithm works

Our parser uses the native DOMParser to build a navigable tree. It then:

  1. Identifies record elements – every direct child of the root XML element is treated as one row.
  2. Collects column names – from child element tags and (optionally) attributes. Attributes are prefixed with @ to avoid name collisions (e.g., @id).
  3. Unifies column set – scans all rows to ensure missing columns become NULL.
  4. Detects data types – values that can be parsed as numbers (integers, floats) are emitted without quotes; strings are escaped and quoted. Boolean strings 'true'/'false' are left as strings (or you can adjust).
  5. Escapes single quotes – replaces ' with '' (standard SQL).
  6. Applies identifier quoting – backticks for MySQL, double quotes for PostgreSQL (configurable).

The result is a batch of INSERT statements that you can directly execute in your database client.

Handling complex XML: nesting, repeated elements, attributes

This converter is designed for flat, record‑oriented XML (like database dumps). For nested elements (e.g., <order><items><item>...</item></items></order>) we recommend using a parent-child conversion strategy. Currently, nested elements are ignored because they would require separate tables. However, attributes are fully supported. The tool shows a warning when nested elements are detected. If you need to process nested structures, consider using an XSLT transformation first.

Step‑by‑step guide (with file upload)

  1. Choose input method: Use the "Manual XML" tab to paste XML directly, or switch to "Upload XML File" to drag & drop or select a file (max 10MB).
  2. Enter the target SQL table name (e.g., users).
  3. Toggle options: include attributes, choose identifier quote style (backticks for MySQL, uncheck for PostgreSQL double quotes).
  4. Click "Convert to SQL" – the INSERT statements appear below.
  5. Copy the SQL and run it in your database client.

Example transformations

Verified with real XML samples; results match the tool's output.

XML snippet Table name Generated INSERT (first row)
<person id="1"><name>Alex</name></person> employees INSERT INTO employees (`@id`, `name`) VALUES ('1', 'Alex');
<product sku="X100"><price>49.99</price></product> products INSERT INTO products (`@sku`, `price`) VALUES ('X100', 49.99);
<log><entry><message>It's working</message></entry></log> logs INSERT INTO logs (`message`) VALUES ('It''s working');
Case Study: Bulk migration from XML exports

A financial firm needed to import 15,000 transaction records from XML files into a PostgreSQL database. Using the file upload tab, an analyst dragged and dropped a 6 MB XML file; the converter generated the INSERT statements in under 2 seconds. The automatic type detection correctly handled decimal amounts and dates (as strings, later cast). The batch was executed via psql, saving hours of manual scripting.

Common pitfalls & best practices

  • Inconsistent columns: If some records have extra elements, the tool adds NULL for missing columns. Always review the output to ensure data integrity.
  • Large XML files: For files >5 MB, the browser may become slow. Consider splitting into smaller chunks.
  • Special characters: XML entities (&, <) are automatically decoded; the resulting SQL contains the actual characters (properly escaped).
  • Attribute vs element name clash: Attributes are prefixed with @ to avoid collisions. If you don't want the prefix, uncheck "Include XML attributes".

Built with database professionals in mind – This tool was developed by the GetZenQuery data team, combining experience in ETL processes, XML processing, and SQL optimization. Reviewed by database administrators and software engineers. Last updated March 2026. We follow OWASP guidelines to prevent XSS and ensure safe client‑side parsing.

Frequently Asked Questions

Basic namespace support: the element's local name is used as column name (prefixes are stripped). Attributes with namespaces are included with the full qualified name if they appear; you may see colons in column names. If that is an issue, preprocess with a find‑and‑replace.

Currently we focus on INSERT generation. However, you can deduce schema from the column list. A future version may offer CREATE TABLE inference based on data types.

They are treated as empty string '' in the SQL (not NULL). To force NULL, omit the element entirely.

Absolutely. All processing happens inside your browser. No data is transmitted over the network. You can use it offline after the page loads.
References: W3C XML Specification; MySQL INSERT syntax; PostgreSQL INSERT; "XML in a Nutshell" by Harold & Means.