Quick reference
| Setting | Value / behavior |
|---|---|
| Identifier quoting | double quotes |
| Missing/null | SQL NULL |
| Execution | never performed |
Input and conversion rules
Enter a non-empty array of row objects and a simple table name containing letters, digits and underscores. The converter builds a union of the object keys, then generates one INSERT statement per row. Missing values and JSON null become SQL NULL. JSON booleans become TRUE or FALSE, numeric values remain numeric, and strings are single-quoted with embedded apostrophes doubled. Nested objects and arrays are stored as JSON text literals rather than expanded into related rows.
Important edge cases
Identifiers use double quotes, following standard SQL and PostgreSQL-style conventions. This is not a universal dialect converter: default MySQL modes, SQL Server settings, column types and backslash-escape rules can require changes. No CREATE TABLE statement is generated, no database connection is made, and the tool does not run the SQL. For application code, prefer parameterized queries. Treat this export as an inspectable migration aid and test it in a disposable database before touching production.
A reliable workflow
First run the built-in example to understand the output structure. Replace it with a small representative sample from your own workflow and inspect every field that has special meaning: identifiers, currency, dates, missing values and nested collections. Then process the complete input, up to two million characters. The result can be copied or downloaded. Keep a separate original because conversion is not always reversible, especially when the target format cannot represent all the distinctions in the source.
Privacy and verification
The transformation runs in your browser using local JavaScript. There is no data-upload request and no account requirement. The page does not save your input to browser storage or place it in a shareable URL. Clearing the form removes the displayed input and result; it does not delete the original file or erase your operating system’s clipboard. Check the receiving program with a small import before loading a complete dataset. If the input is untrusted, retain formula protection where available and avoid running exported commands without review.
Frequently asked questions
Are my values uploaded?
No. The conversion is performed in the page.
Is the conversion lossless?
Not always. Review the edge cases above, especially missing values, nested data and number precision.
Why did validation fail?
Check syntax, expected input shape and the specific row or parser error shown by the tool.
About this tool
Built and maintained by Mihai at Void Fabric. This page documents the behavior of the current implementation. Found an error or an unclear assumption? Send a reproducible example with sensitive values removed.
Reference: Void Fabric field notes · Testing and editorial policy