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Convert CSV to SQL.

Drop a CSV, get correct CREATE TABLE + INSERT statements. Column types inferred from your data — not just VARCHAR everywhere.

To convert CSV to SQL, drop or paste a CSV file — csvtodashboard parses it into rows and columns in your browser, then emits CREATE TABLE plus INSERT statements. Column types are inferred from the data and string values are quoted and escaped, so the statements run as written. Nothing is uploaded; the whole conversion runs on your device.

01 · How it works

Three steps, then done.

Most CSV-to-SQL tools output `CREATE TABLE foo (col1 VARCHAR(255), col2 VARCHAR(255), ...)` — every column as a string. That's wrong, and it forces you to rewrite the schema by hand. Ours actually reads each column and picks the right SQL type: `INT` for whole numbers, `DECIMAL(p,s)` for fractional, `DATE` for date columns, `BOOLEAN` for true/false, `VARCHAR(n)` sized to the actual content.

i. drop

Drop your file

Drag from Finder, click to choose, or paste data directly into the input pane.

ii. detect

We read the shape

Column types are inferred from the data so the output is correctly typed — not strings everywhere.

iii. use it

Copy, download, or dashboard

Copy the SQL, download it as a file, or hit 'Build dashboard' to chart what's in your data.

02 · Why ours

Smart SQL conversion by default.

Most free SQL converters output a string for every value and bury your file in an upload form. Ours infers types from your data and runs entirely in your browser, so the SQL looks like what you'd write by hand.

  • 01

    Correct types

    Numbers stay numbers, dates stay dates, booleans stay booleans — no quoted-string SQL output.

  • 02

    Local-first

    Your file is parsed and converted in your browser. Nothing is uploaded; verify in DevTools → Network.

  • 03

    Fails loudly

    Malformed input gives a clear, specific error instead of silently wrong SQL — so you can trust the result.

  • 04

    One click to a dashboard

    Every conversion keeps a tabular copy, so you can send the data straight to our visualization tool to chart it.

"Needed a quick SQL conversion and ended up making a dashboard. Didn't expect that."
— the typical csvtodashboard arc
Good to know

csv to sql notes.

Format-specific details worth knowing before you convert CSV to SQL.

  • Types are inferred

    Column types (INTEGER, REAL, TEXT) come from the data, not VARCHAR everywhere, so the generated CREATE TABLE matches your actual values.

  • Quotes are escaped

    String values are single-quoted with embedded quotes doubled, as in O''Brien — the standard SQL escape — so the INSERTs run as written.

  • Blanks become NULL

    Empty cells are emitted as NULL rather than an empty string; rename any header that clashes with a SQL reserved word before importing.

03 · FAQ

csv to sql questions.

How do you decide which SQL type to use?
For each column, we scan all non-empty values. If they're all integers, INT (or BIGINT if values exceed 2^31). If they're all numeric, DECIMAL with precision/scale matching the data. If they parse as dates, DATE (or TIMESTAMP if there's a time component). If they're true/false-style, BOOLEAN. Otherwise VARCHAR with a length 10 chars longer than the longest cell.
The CREATE TABLE syntax is ANSI-standard SQL — works in PostgreSQL, MySQL, SQLite, SQL Server, Oracle. The INSERT statements are also standard. We don't generate database-specific features like AUTO_INCREMENT or SERIAL.
Yes — there's a text field above the output where you can set it. Default is `csv_data`.
By default, 100 rows per INSERT statement. You can change the batch size if you want one INSERT per row or larger batches.
Empty cells (and explicit NULL-looking values) become SQL `NULL`, not the literal string 'NULL'.