Is converting Parquet to SQL Server 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 SQL Server?

Yes — that is the point. Whole numbers, decimals, dates and booleans are mapped to real SQL Server 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 SQL Server

Upload a .parquet file and get back a SQL Server SQL script you can load straight into your database. 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 SQL Server

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

Your data	SQL Server type
Whole number	BIGINT
Decimal (money)	DECIMAL(10,2)
Floating point	FLOAT
True / false	BIT
Date	DATE
Date and time	DATETIME2
Short text	NVARCHAR(255)
Long text	NVARCHAR(MAX)
Binary data	VARBINARY(MAX)

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.

How names and bytes are written

mssql is the short name the drivers use - the ODBC DSN, SQLAlchemy's mssql+pyodbc, the container image. What it produces is ordinary T-SQL text, and the details worth checking before you run it are how it writes names and how it writes raw bytes.

→Identifiers are wrapped in square brackets rather than double quotes, and a bracket inside a source name is turned into an underscore before the wrapping goes on: a column named Order]Date is created as [Order_Date], so a bracket in your data can never close a name early.
→The identifier cap is 128 characters, high enough that almost every source name survives untouched - one that Oracle would have to cut at 30 arrives here whole.
→Binary columns are VARBINARY(MAX) and their values are written as bare 0x hex literals, with no quotes around them and no conversion function wrapped over them.

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 SQL Server

→String literals carry the N prefix, so non-ASCII text survives whatever collation the database uses.
→Timestamps become DATETIME2. T-SQL’s TIMESTAMP is a row-version counter, not a point in time.
→Identity columns are wrapped in SET IDENTITY_INSERT so explicit key values load.
→Statements are separated with GO in batches.

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 SQL Server:

  sqlcmd -S HOST -U USER -P PASSWORD -d DATABASE -i dump.sql

Notes:

  - Text columns are NVARCHAR and literals carry the N prefix, so
    non-ASCII data survives regardless of database collation.
  - Timestamps are DATETIME2. T-SQL's TIMESTAMP type is a row
    version, not a point in time.

Questions

Is converting Parquet to SQL Server 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 SQL Server?: Yes — that is the point. Whole numbers, decimals, dates and booleans are mapped to real SQL Server 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.