Turning one INSERT statement into a JSON object
"INSERT INTO users (id, name) VALUES (1, 'Ada');" converts into the JSON object {"id": 1, "name": "Ada"} -- column names from the parenthesized list become JSON keys, matched positionally to the corresponding values.
Notice the numeric value (1) stays a JSON number while the quoted value ('Ada') becomes a JSON string -- this converter distinguishes SQL's quoted-string versus unquoted-numeric convention and maps each to the appropriate JSON type rather than treating everything as text.
This positional matching (first column name maps to first value, second to second, and so on) depends entirely on the column list and value list having the same order and count -- a mismatch between the two would produce incorrectly paired keys and values.
The narrow, specific format this converter understands
Understands INSERT INTO t (a,b) VALUES (...) or col=val lines only. Not a SQL engine. This recognizes exactly two input shapes: a standard INSERT INTO table (columns) VALUES (values) statement, or simple col=val lines -- it isn't a general SQL parser and won't handle SELECT statements, multi-row INSERT VALUES lists, UPDATE statements, or more complex SQL syntax.
This performs pure text pattern-matching against those two specific formats -- it doesn't connect to or execute against an actual database, and it has no awareness of a real table's schema, column types, or constraints beyond what's directly visible in the pasted SQL text.
Complex values (nested function calls, subqueries as a value, or SQL expressions instead of literal values) aren't handled -- this tool is built for straightforward literal INSERT statements, not dynamic SQL expressions.
Related data-format conversion tools
For a full table (multiple rows) rather than a single INSERT statement, the CSV to JSON Converter handles the more common bulk-conversion case.
If you're going the other direction -- JSON data into a SQL INSERT statement -- the CSV to SQL Insert Generator handles that reverse conversion from CSV.
Frequently Asked Questions (FAQ)
How does the converter know which value belongs to which column?
It matches them positionally: the first column name in the parentheses pairs with the first value, the second with the second, and so on. The column list and value list need to have matching order and count for this to produce correct results.
Why does 1 become a JSON number but 'Ada' becomes a JSON string?
SQL uses quotes to denote string literals, so an unquoted numeric value like 1 is recognized and output as a JSON number, while a quoted value like 'Ada' is recognized and output as a JSON string -- matching each SQL literal type to its equivalent JSON type.
Can this convert a SELECT statement's results into JSON?
No. Understands INSERT INTO t (a,b) VALUES (...) or col=val lines only. Not a SQL engine. It only recognizes INSERT INTO statements or simple col=val lines. It doesn't execute queries or process SELECT statement output.
Does this connect to a real database to validate the table structure?
No. It's pure text pattern-matching on the SQL you paste in. It has no connection to any actual database and no awareness of a real table's schema beyond what's directly visible in the input text.
Can this handle multiple rows in one VALUES clause?
It's built around a single row of values matched to a single column list. Multi-row INSERT statements with several value tuples aren't part of the specific format this converter is designed to parse.
