About

Migrating data between systems often requires converting raw datasets into executable SQL commands. This tool automates the creation of INSERT INTO statements from CSV or JSON sources. It addresses the common pain points of manual query writing: syntax errors caused by unescaped characters, tedious formatting of large datasets, and dialect-specific quoting rules.

Whether you are populating a testing database or migrating production data, this generator ensures your queries are syntactically correct and safe from basic injection risks by properly escaping special characters like single quotes and backslashes.

Formulas

The generator parses raw text input using a state-machine approach to handle delimiters and qualifiers. The core logic follows this sequence:

Step 1: Parsing. The engine identifies the input format (CSV or JSON). For CSV, it splits by newline \n and respects comma delimiters inside quotes.
Step 2: Mapping. Header rows are sanitized to become column names (e.g., User Name → user_name).
Step 3: Sanitization. Values are scanned for dialect-specific reserved characters. For example, in SQL, O'Reilly becomes O''Reilly.
Step 4: Construction. The final query is built using the standard syntax:
INSERT INTO table (col1, col2) VALUES (val1, val2);

Reference Data

SQL Dialect	Identifier Quote	String Quote	Batch Support	Boolean Literal
MySQL / MariaDB	` (Backtick)	' (Single)	Multi-row VALUES	1 / 0
PostgreSQL	" (Double)	' (Single)	Multi-row VALUES	TRUE / FALSE
SQL Server (T-SQL)	[] (Brackets)	' (Single)	Select UNION ALL	1 / 0
SQLite	" (Double)	' (Single)	Multi-row VALUES	1 / 0

Frequently Asked Questions

The generator detects standard null indicators. If a cell in CSV is empty or explicitly contains the text "NULL" (case-insensitive), the generated SQL will use the native SQL NULL keyword without quotes, rather than inserting an empty string.

While standard SQL is universal, quoting identifiers and handling booleans varies. MySQL uses backticks for table names, while PostgreSQL uses double quotes. Choosing the wrong dialect can cause syntax errors during execution.

Yes, the script processes data in client-side memory. It includes a "Batch Size" feature to break extremely large datasets into multiple INSERT statements (e.g., 100 rows per query) to avoid hitting database server packet limits.