Convert Parquet to PGSQL
Upload a .parquet file and get back a PGSQL SQL script you can load straight into your database. Types are preserved rather than flattened to text. Free, no registration, up to 10MB.
Click to upload or drag and drop
CSV, Excel, SQLite, SQL, DBF (max 10 MB)
How your data is typed in PGSQL
Generated from the converter's own PGSQL type mapping — this is what it actually emits, not an example.
| Your data | PGSQL type |
|---|---|
| Whole number | BIGINT |
| Decimal (money) | NUMERIC(10,2) |
| Floating point | DOUBLE PRECISION |
| True / false | BOOLEAN |
| Date | DATE |
| Date and time | TIMESTAMP |
| Short text | TEXT |
| Long text | TEXT |
| Binary data | BYTEA |
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.
Loading into an application's database
PGSQL is the name PostgreSQL wears inside application code: PHP's pgsql extension, Laravel's pgsql connection driver, the pdo_pgsql DSN prefix. If that is where you met the name, the database you are loading into probably belongs to a framework, which changes what to watch for.
- →The script creates its own tables. Point it at a schema your migrations own and the next migration run and this file will disagree about who defines the table - load into an empty schema, or a database of its own, and point the application at that.
- →Because every identifier is double-quoted, the case the source used is the case that gets stored. A column that arrives as "CustomerID" has to be quoted in your queries too: an unquoted CustomerID folds to customerid and is not found.
- →No FOREIGN KEY, index or view statement is generated at all, so a framework that introspects the database finds unrelated tables. Declare the relations in your models, or add them with ALTER TABLE once the rows are 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 PGSQL
- →Backslashes are left alone, because PostgreSQL treats them as ordinary characters — doubling them would corrupt every Windows path.
- →Auto-increment columns become GENERATED BY DEFAULT AS IDENTITY.
- →Binary data is written as bytea, and identifiers respect the 63-character limit.
What you get
A ZIP containing dump.sql, plus a README with the exact command to load it. If anything about your data needed a judgement call, a _warnings.txt explains it.
Load this dump into PostgreSQL: psql -U USER -d DATABASE -f dump.sql Create the database first if it does not exist: createdb -U USER DATABASE
Questions
- Is converting Parquet to PGSQL 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 PGSQL?
- Yes — that is the point. Whole numbers, decimals, dates and booleans are mapped to real PGSQL 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.