| title | Supported file formats by copy activity in Azure Data Factory |
|---|---|
| titleSuffix | Azure Data Factory & Azure Synapse |
| description | This topic describes the file formats and compression codes that are supported by copy activity in Azure Data Factory and Azure Synapse Analytics. |
| author | jianleishen |
| ms.subservice | data-movement |
| ms.custom | synapse |
| ms.topic | concept-article |
| ms.date | 02/13/2025 |
| ms.author | jianleishen |
Supported file formats and compression codecs by copy activity in Azure Data Factory and Azure Synapse pipelines
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This article applies to the following connectors: Amazon S3, Amazon S3 Compatible Storage, Azure Blob, Azure Data Lake Storage Gen1, Azure Data Lake Storage Gen2, Azure Files, File System, FTP, Google Cloud Storage, HDFS, HTTP, Oracle Cloud Storage and SFTP.
[!INCLUDE data-factory-v2-file-formats]
You can use the Copy activity to copy files as-is between two file-based data stores, in which case the data is copied efficiently without any serialization or deserialization.
In addition, you can also parse or generate files of a given format. For example, you can perform the following:
- Copy data from a SQL Server database and write to Azure Data Lake Storage Gen2 in Parquet format.
- Copy files in text (CSV) format from an on-premises file system and write to Azure Blob storage in Avro format.
- Copy zipped files from an on-premises file system, decompress them on-the-fly, and write extracted files to Azure Data Lake Storage Gen2.
- Copy data in Gzip compressed-text (CSV) format from Azure Blob storage and write it to Azure SQL Database.
- Many more activities that require serialization/deserialization or compression/decompression.
See the other Copy Activity articles: