Convert Parquet to Postgres
Upload a .parquet file and get back a Postgres 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 Postgres
Generated from the converter's own Postgres type mapping — this is what it actually emits, not an example.
| Your data | Postgres 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.
The oldest PostgreSQL this loads into
Postgres is the informal spelling and the one most people type. Since the name says nothing about a version, the useful question for this page is which server releases the generated script runs on, and that is decided by the newest piece of syntax in it.
- →The identity clause on auto-increment columns is the newest thing in the file, and it arrived in release 10. That is the floor for loading the script unedited.
- →Everything else is far older: the hex escape the script uses for binary values has been accepted since 9.0, and jsonb, which is what a JSON column is declared as, since 9.4.
- →On a server below the floor the script still loads if you delete the identity clauses by hand. The columns keep every value they were given, because each INSERT names them explicitly; they simply stop assigning new ones.
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 Postgres
- →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 Postgres 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 Postgres?
- Yes — that is the point. Whole numbers, decimals, dates and booleans are mapped to real Postgres 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.