James Allman | JA Technology Solutions LLC
SQL INSERT Converter
Extract rows from SQL INSERT statements and convert them to CSV, Excel, JSON, and 8 other formats.
SQL INSERT Converter
Paste SQL INSERT statements — single-row or multi-row VALUES, with or without an explicit column list — or upload a `.sql` file and convert the extracted rows to CSV, TSV, pipe-delimited text, JSON, JSONL, Excel, YAML, XML, Markdown table, or HTML table. Handles quoted strings (single and double, with `''` and `\'` escapes), numbers, `NULL`, `TRUE` / `FALSE`, multi-tuple `VALUES (…), (…), (…);` syntax, optional schema prefixes on the table name, quoted/backticked/bracketed identifiers (`"col"`, `` `col` ``, `[col]`), line comments (`-- …`), and block comments (`/* … */`). Useful for pulling data out of database dumps, examining seed files, or moving between databases via intermediate CSV/Excel. Heavy parsing and output generation run in a Web Worker so the UI stays responsive on large dumps; you can cancel an in-progress conversion at any time. Runs entirely in your browser; pasted SQL and uploaded files never leave your machine.
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Where SQL INSERT Files Come From
SQL dump files — produced by `pg_dump`, `mysqldump`, `sqlite3 .dump`, SQL Server export wizards, and most ORM seed-file generators — are the most portable way to move data between database platforms. They are also the most common form of data exchange between people who have access to a database and people who do not, because nearly every relational database speaks the same `INSERT INTO … VALUES (…)` syntax with only minor dialectal differences. This tool turns those statements back into rows so you can inspect them in a spreadsheet, hand them to a non-SQL system, or reshape them for a different schema.
What Dialectal Variation Looks Like
The parser handles the common variations: explicit column lists (INSERT INTO t (a, b) VALUES (…)) and bare inserts (INSERT INTO t VALUES (…)), single-quoted string literals with `''` doubled-quote escape, double-quoted strings (some dialects), backslash escapes (`\\'`, `\\n`), unquoted numbers and booleans, `NULL`, multi-row `VALUES (…), (…), (…);` tuples, schema-qualified table names (public.orders), quoted identifiers ("col", `col`, [col]), and inline `--` / `/* … */` comments. What is intentionally not handled is `DEFAULT`, function calls in value position (NOW(), UUID()), and subselects — those need actual SQL execution against a database, not regex extraction.
When You Need Real SQL Execution
This tool extracts row-data from `INSERT` statements that are already fully resolved. If your migration plan involves running schema-creating DDL, applying defaults, evaluating expressions, or merging into existing tables under foreign-key constraints, the right move is a real database load — not a paste. I build database migration plans that include schema reconciliation, data validation, dependency-aware load order, rollback strategies, and downtime planning. Need help? Migration services · ETL and data pipelines. Have a question? Ask James.
All tools run entirely in your browser. Your data never leaves your machine.