JSON to SQL INSERT Converter

The JSON to SQL INSERT Converter is a free online tool that convert json arrays or objects to sql insert statements with dialect-aware quoting (mysql, postgresql, sqlite, sql server), bulk or per-row output, and optional create table inference.. It runs entirely in your browser with no installation or sign-up needed.

MySQL, PostgreSQL, SQLite, and SQL Server. Identifier quoting switches automatically (backticks/double-quotes/brackets) and booleans become 1/0 or TRUE/FALSE per dialect.

Yes. Enable Include CREATE TABLE to infer a schema from the first 100 rows — INT, DECIMAL, BOOLEAN, DATETIME, bucketed VARCHAR(n), or TEXT — with nullable detection.

Strings wrap in single quotes with standard doubled-quote or legacy backslash escaping. Nulls emit NULL or empty string. ISO-8601 dates are detected and quoted as DATETIME/TIMESTAMP.

Yes, the JSON to SQL INSERT Converter is 100% free with no registration, no hidden fees, and no usage limits. All processing happens locally in your browser, ensuring complete privacy.

Absolutely. The JSON to SQL INSERT Converter processes everything client-side in your browser. No data is uploaded to or stored on any server. Your content remains private on your device at all times.

Yes, the JSON to SQL INSERT Converter is fully responsive and works on smartphones and tablets. You can use it on any device with a modern web browser -- no app download required.

No account or registration is needed. Simply open the JSON to SQL INSERT Converter in your browser and start using it immediately. There are no sign-up walls or usage restrictions.

Simply enter your input in the provided field, adjust any settings to your preference, and the tool will process it instantly. You can then copy the result to your clipboard or download it.

The JSON to SQL INSERT Converter works in all modern browsers including Chrome, Firefox, Safari, Edge, and Opera. For the best experience, use the latest version of your preferred browser.

A bulk insert lists every row inside a single statement — INSERT INTO table (cols) VALUES (...), (...), (...); — so all rows load in one round trip. It is more compact and usually the fastest way to seed a table, which is why this converter uses it by default. The one-per-row style emits a separate INSERT INTO ... VALUES (...); line for each record. That output is longer but easier to read, diff in version control, or run partially when you only want to apply some rows or skip a record that errors. Both produce identical data; the choice is about execution speed versus granular control. Some database clients also cap how many rows a single statement can hold, so per-row output sidesteps that limit. Switch between the two with the Statement style toggle and the SQL regenerates instantly.

Single quotes inside text are the classic cause of broken INSERT scripts — a name like O'Brien would otherwise close the string early and corrupt the statement. This tool escapes them automatically. With standard mode (the default), every embedded single quote is doubled, so O'Brien becomes 'O''Brien', which is valid ANSI SQL accepted by MySQL, PostgreSQL, SQLite, and SQL Server. If your engine expects legacy backslash escaping instead, switch to backslash mode and the same value becomes 'O\'Brien', with literal backslashes also escaped. Column and table identifiers get their own quoting — backticks, double quotes, or square brackets per dialect — and any quote characters inside those names are escaped too. The result is that messy real-world data with apostrophes, quotation marks, and special characters converts into a script you can run without manual cleanup.

Real exports are often uneven — one record has a phone field, the next does not. This converter handles that by taking the union of every key across all rows, listed in first-seen order, and using that combined set as the column list. Any row missing a given key has NULL (or an empty string, depending on your NULL handling setting) inserted for that column, so every VALUES tuple stays aligned with the column header. That means partial or inconsistent objects still line up into one clean table instead of failing. The one case it rejects is when an item in the array is not an object at all — a bare number, string, or nested array. When that happens, it stops and tells you the exact index so you can fix the source. Paste your mixed JSON and the column union is built for you automatically.

Relational columns hold scalar values, so a nested object or array cannot map to a normal column directly. When the converter meets a value that is itself an object or array, it serializes that value back to a compact JSON string and inserts it as a quoted text value, with the same escaping applied as any other string. So a field like {"tags":["a","b"]} becomes the literal string '["a","b"]' in the INSERT. If you also generate a CREATE TABLE, those columns are typed as TEXT (or NVARCHAR(MAX) on SQL Server) to hold the serialized JSON. This keeps your data intact and runnable, though it does not flatten nested structures into separate columns or related tables — that normalization is a design decision only you can make. For Postgres JSON or JSONB columns, paste the generated text and adjust the column type to suit.

Each database has its own rules for identifiers and certain value types, and a script written for one engine often fails on another. This converter adjusts the output per dialect so it runs as-is. Identifier quoting changes: MySQL wraps table and column names in backticks, PostgreSQL and SQLite use double quotes, and SQL Server uses square brackets. Boolean values also differ — true and false become 1 and 0 on MySQL and SQLite, but TRUE and FALSE on PostgreSQL and SQL Server. Inferred CREATE TABLE types shift too, such as TINYINT(1) for a MySQL boolean versus a native BOOLEAN on Postgres, or NVARCHAR on SQL Server versus VARCHAR elsewhere. String escaping stays standard ANSI by default across all four. Pick your target from the Dialect toggle before copying so the statements match the database you are loading into.