What is a JSON to SQL Converter?
A JSON to SQL converter turns an array of JSON objects into the SQL statements a relational database needs to store them. It reads the keys of your objects as column names and each object as a record, then emits a CREATE TABLE statement that defines the columns and a set of INSERT statements that load the data. The result is a script you can paste into a database client, save as a migration, or pipe into mysql, psql, or sqlite3 to build and populate a table in one step.
This is worth automating because JSON and SQL disagree on almost everything. JSON has objects, arrays, and native booleans; a SQL table has fixed columns and typed values. Converting by hand means deciding a column type for every field, quoting every string, doubling embedded quotes so the statement does not break, leaving numbers and booleans unquoted, turning missing keys into NULL, and serializing nested objects into text. Miss one rule across a few hundred records and the whole batch fails to run. This tool applies those rules consistently: it scans every object, infers whether each column holds integers, decimals, booleans, JSON, or text, and quotes identifiers the way your chosen dialect expects, using backticks for MySQL and double quotes for PostgreSQL, SQLite, and standard SQL.
It handles the awkward parts of real data too. Objects in the array do not have to share the same keys: the columns are the union of every key seen, and any object missing a key gets NULL for that column. Nested objects and arrays are stored as JSON text, mapped to the native JSON type on MySQL and JSONB on PostgreSQL. A field that is a number in one record and a string in another falls back to a text column so the INSERT still runs rather than failing on a type mismatch.
Everything runs in your browser. The JSON is parsed and the SQL is generated locally in JavaScript, so nothing is uploaded, logged, or stored. That matters when the data is an API response, a database export, or anything with real identifiers and emails in it. Because the work is local, the tool keeps functioning offline once the page has loaded and stays fast on large payloads since there is no network round trip.
How to use the JSON to SQL Converter?
Paste your JSON
Paste an array of objects, such as [{ "id": 1, "name": "Ada" }], or a single object. Press Load Sample to see the expected shape. Each object becomes one row.
Set the table name and dialect
Type the target table name and pick MySQL, PostgreSQL, SQLite, or standard SQL. The dialect controls identifier quoting and the type and boolean syntax used in the output.
Choose the output options
Decide whether to include a CREATE TABLE statement, infer column types from the data, and emit one multi-row INSERT or one statement per row.
Copy the SQL
Read the generated CREATE TABLE and INSERT statements, then copy them. Paste the script into your database client or run it from the command line to build and load the table.
Key Features
CREATE TABLE with inferred types
Every object is scanned and each column is typed as integer, decimal, boolean, JSON, or text, so the generated CREATE TABLE matches the data instead of forcing everything into a single string column.
Four SQL dialects
Output targets MySQL, PostgreSQL, SQLite, or standard SQL. The dialect sets identifier quoting, the numeric and boolean type names, and the native JSON type used for nested values.
Handles uneven objects
Objects do not need identical keys. Columns are the union of all keys in first-seen order, and any object missing a key gets NULL for that column.
Nested values as JSON
Arrays and nested objects are serialized to JSON text and stored in a JSON column on MySQL, a JSONB column on PostgreSQL, or a TEXT column elsewhere.
Frequently Asked Questions
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