Extract data from SQL INSERT statements and convert it to JSON format. Ideal for recovering data from dumps or migrating to NoSQL.
Click "Convert" to generate JSON
Useful when you have SQL seed files, migration snippets, or backup extracts and need the row data in JSON quickly.
A practical bridge when backend or test data already exists as SQL but frontend, scripts, or docs need JSON instead.
The converter needs column names to map values into JSON keys. Statements like INSERT INTO users VALUES (...) are ambiguous and should be expanded first.
Quoted strings, numbers, booleans, and NULL values map well to JSON primitives, which makes this tool effective for normal seed data and dumps.
Values such as NOW() or UUID() are not executed because the tool has no database context. Review those fields manually if downstream JSON consumers expect concrete values.
Extracting data from database dumps or SQL scripts does not have to be a manual nightmare. Our SQL to JSON Converter parses your INSERT statements and transforms the values into structured JSON objects. This is essential for developers migrating legacy data to NoSQL databases, building REST API responses, or simply inspecting data in a human-readable format.
Relational data (rows/columns) often needs to be consumed by modern web applications or document stores (like MongoDB or Firestore). Instead of writing custom scripts to parse your SQL dumps, this tool allows you to:
INSERT INTO table (...) VALUES ...).(1, 'a'), (2, 'b') into an array of objects.INSERT statement.INSERT statement with specified columns (e.g., INSERT INTO users (id, name) VALUES...)..json file for immediate use.We treat SQL as a structured language, not just string manipulation. Here is how we ensure accuracy:
'value' and standard SQL escaping ('' for a single quote).TRUE, FALSE, 1, and 0 are mapped to JSON booleans where appropriate.NULL keywords become null (not string "null").While powerful, this tool is designed for standard data dumps. Be aware of:
0x... values or binary blobs may not convert cleanly to JSON strings without encoding (e.g., Base64), which we do not currently perform.NOW() or UUID(), we treat them as strings because we cannot evaluate them without a running database.INSERT INTO t (col1, col2) to map values correctly. We cannot guess column names from values alone.NULL?Yes! SQL NULL values are converted to native JSON null.
This tool is specifically designed for INSERT statements. It does not execute SELECT queries. If you have a SELECT result, export it as CSV and use our CSV tool (or convert CSV to JSON).
e.g., INSERT INTO users VALUES (1, 'Alice'). Currently, this is not supported because the tool does not know the column names. You must specify columns: INSERT INTO users (id, name)....
Since processing happens in your browser, the limit is your available RAM. Text files up to 10-20MB usually process instantly. Larger files may freeze the browser tab temporarily.
Good follow-up when you need to move between relational rows and JSON documents without losing track of structure.
Relevant when converting SQL inserts to JSON could expose sensitive data that should be transformed before reuse or sharing.
Useful when SQL generation and extraction are becoming part of a larger automation flow.
Helpful when JSON output from SQL inserts becomes part of your test fixture workflow.
Use this path when the goal is moving relational seed data into JSON that frontend tests, docs, or mock APIs can consume directly.
Relevant when the SQL dump contains realistic user or business data and the JSON output might leave the database boundary.
Choose this route when SQL, JSON, CSV, and schema decisions are all part of the same migration or import project.
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