JSON Sorter
Sort JSON object keys alphabetically at every level, or sort arrays by a field.
CSV to SQL
Turn a CSV export into INSERT statements, with column types inferred.
Quick Tool Overview
The CSV to SQL converter turns a spreadsheet export into INSERT statements: the header row becomes the column list, quotes are escaped, blanks become NULL, and column types are decided from the whole column rather than cell by cell.
- What it does
- Generates SQL INSERT statements from CSV
- You give it
- CSV with a header row
- You get back
- INSERT statements, optionally with a CREATE TABLE
- Best for
- Loading a spreadsheet or export into a database
About the CSV to SQL
Loading a spreadsheet export into a database usually means either an import wizard you do not trust or statements you write by hand. This generates the statements: the header row becomes the column list, each data row becomes a set of values.
The escaping and typing are where hand-written SQL goes wrong. Single quotes inside a value are doubled, which is the standard escape and works in every major database. Column types are decided from the whole column rather than cell by cell, so one blank does not turn a numeric column into text. Blank cells become NULL rather than empty strings. You can emit one statement per row, or a single batched insert that loads far faster, plus an optional CREATE TABLE.
Key features of the CSV to SQL
RFC 4180 reading
A quoted field containing commas, line breaks or doubled quotes is read as one value, which is where naive splitting corrupts a row.
Types from the whole column
One blank cell does not turn a numeric column into text, because the type is decided from every value at once.
Blanks become NULL
An empty cell is written as NULL rather than an empty string, which is almost always what a database import should mean.
Safe column names
Spaces and punctuation in a header become underscores and a leading digit is prefixed, so the statement parses.
Batched or single
One multi-row INSERT for a fast bulk load, or a statement per row when you need to run them selectively.
How to use the CSV to SQL
-
1
Paste your CSV
Include the header row — it becomes the column names.
-
2
Name the table
Set the target table and choose your SQL dialect for the right quoting.
-
3
Choose the statement style
One INSERT per row for readability, or a single batched insert for a fast load.
-
4
Run the SQL
Add the CREATE TABLE first if the table does not exist yet.
Frequently asked questions
The reader follows RFC 4180, so a quoted field containing commas, line breaks or doubled quotes is read as one value rather than being split.
From every value in the column at once. A column whose non-blank values are all numeric becomes BIGINT or DOUBLE; all true/false becomes BOOLEAN; anything else becomes VARCHAR(255).
They become NULL rather than an empty string, which is almost always what a database import should mean.
For a bulk load, substantially — one statement for a thousand rows is far faster than a thousand statements. Use single rows when you need to run them selectively.
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