Is converting Parquet to DuckDB free?

Yes. Files up to 10MB convert free with no account. There is a limit of five conversions per day per IP address.

Will my Parquet data keep its types in DuckDB?

Yes — that is the point. Whole numbers, decimals, dates and booleans are mapped to real DuckDB types rather than everything becoming text. The mapping table above shows exactly what you get.

Do you store my file?

No. The file is written to a temporary directory, converted, and the directory is deleted as soon as your download has been sent.

Convert Parquet to DuckDB

Upload a .parquet file and get back a DuckDB file. Types are preserved rather than flattened to text. Free, no registration, up to 10MB.

1Upload your file

Click to upload or drag and drop

CSV, Excel, SQLite, SQL, DBF (max 10 MB)

2Choose target format

How your data is typed in DuckDB

Generated from the converter's own DuckDB type mapping — this is what it actually emits, not an example.

Your data	DuckDB type
Whole number	BIGINT
Decimal (money)	DECIMAL(10,2)
Floating point	DOUBLE
True / false	BOOLEAN
Date	DATE
Date and time	TIMESTAMP
Short text	VARCHAR
Long text	VARCHAR
Binary data	BLOB

Working from a .parquet file

Parquet is the one source here that arrives with a complete, machine-readable schema, so the conversion is a translation rather than an investigation. The interesting question is what Parquet can express that a SQL table cannot.

→Lists, structs and maps have no scalar equivalent in a relational target, so those columns are carried across as JSON text instead of being exploded into invented columns.
→Integer widths are kept rather than widened: int8 and int16 become a 16-bit column and int32 a 32-bit one, so the target schema stays as tight as the file was.
→A Parquet dataset is usually a directory of part files with partition keys encoded in directory names like year=2024/. One file is read, and a column that exists only as a directory name is not inside it.
→Rows are streamed in batches of 10,000, so a wide file never has to be held in memory all at once.

Decimals and text in the .duckdb file

DuckDB takes the source's declared types more nearly unchanged than any other target here, which makes the two places where it cannot the things worth reading: the width of a decimal, and the length of a string.

→DECIMAL tops out at 38 digits, so a wider source column is clamped rather than refused: an Oracle NUMBER(50,10) is created here as DECIMAL(38,10), and the scale is never allowed to grow past the precision holding it.
→A decimal that declared no scale gets six places for its fraction rather than none, inside that same rule: a source precision of 10 becomes DECIMAL(10,6), one of 5 becomes DECIMAL(5,5), and one that declared no precision either becomes DECIMAL(18,6).
→Strings become VARCHAR with no length attached to them. DuckDB's VARCHAR is unbounded, so no column has to be sized in advance and no row can be turned away for being longer than the column it goes in.

Reading Parquet

→Parquet carries a full schema, so nothing is guessed — types, decimal precision and nullability are read directly.
→Decimal columns keep their exact precision and scale.

Writing DuckDB

→A real .duckdb file, not a script — open it straight away with the DuckDB CLI.
→DuckDB has genuine DECIMAL and BOOLEAN types, so nothing is flattened on the way in.

What you get

A ZIP containing database.duckdb. If anything about your data needed a judgement call, a _warnings.txt explains it.

Questions

Is converting Parquet to DuckDB free?: Yes. Files up to 10MB convert free with no account. There is a limit of five conversions per day per IP address.
Will my Parquet data keep its types in DuckDB?: Yes — that is the point. Whole numbers, decimals, dates and booleans are mapped to real DuckDB types rather than everything becoming text. The mapping table above shows exactly what you get.
Do you store my file?: No. The file is written to a temporary directory, converted, and the directory is deleted as soon as your download has been sent.