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dpombal
Post Partisan
Post Partisan

Different ways of getting data from SAP S/4HANA Cloud Private

Hi all,

A customer question about different limitations of getting data from SAP S/4HANA Cloud Private into Microsoft PowerBI, Notebooks...Dataflows. They are worried about the possibility of not having acccess.

 

Now they are using SAP S4/HANA Cloud Private 2022 (RISE) and they are planning to move to SAP S/4HANA 2025

 

which are the different options to get data from this brand new SAP products

  • Notebooks of Python/pyspark??
  • Data Factory??
  • Dataflows??
  • Import/Direct Query from Power BI? I have worked many times with Power BI SAP Hana connector..

 

 

 

 

Thanks

1 ACCEPTED SOLUTION

Hi @dpombal ,

 

For ETL tasks involving SAP HANA data using Python or PySpark, here are the recommended approaches:

  • Python: The best option is SAP’s official hdbcli library, which you can install via pip install hdbcli. It provides reliable and efficient access to SAP HANA, allowing you to run SQL queries and extract data smoothly.
  • PySpark: Use the SAP HANA JDBC driver (ngdbc.jar) to connect Spark directly to SAP HANA through JDBC. This method works well for large-scale data processing, especially in environments like Azure Databricks or Synapse notebooks. Just make sure to upload the driver and properly configure the connection settings.

Also, be sure that network access and permissions are correctly set up. And don’t forget to keep an eye on the SAP S/4HANA 2025 release notes, as they may include important updates affecting connectivity.

 

If this post helps, then please give us Kudos and consider Accept it as a solution to help the other members find it more quickly.

 

Thankyou.

 

 

View solution in original post

4 REPLIES 4
dpombal
Post Partisan
Post Partisan

Most important part is doing ETL process reading from SAP and writing into an Azure SQL Database or for example a Fabric Data Warehouse, so for example Azure Data Factory and Notebooks (Python or PySpark) are the most professional and best options.

 

Which are the recommended libraries for reading sap hana in python/pyspark?

 

Release notes 2025 should be important to review.

 

 

Regards

 

 

 

 

 

 

Hi @dpombal ,

 

For ETL tasks involving SAP HANA data using Python or PySpark, here are the recommended approaches:

  • Python: The best option is SAP’s official hdbcli library, which you can install via pip install hdbcli. It provides reliable and efficient access to SAP HANA, allowing you to run SQL queries and extract data smoothly.
  • PySpark: Use the SAP HANA JDBC driver (ngdbc.jar) to connect Spark directly to SAP HANA through JDBC. This method works well for large-scale data processing, especially in environments like Azure Databricks or Synapse notebooks. Just make sure to upload the driver and properly configure the connection settings.

Also, be sure that network access and permissions are correctly set up. And don’t forget to keep an eye on the SAP S/4HANA 2025 release notes, as they may include important updates affecting connectivity.

 

If this post helps, then please give us Kudos and consider Accept it as a solution to help the other members find it more quickly.

 

Thankyou.

 

 

We need to be careful about SAP S/4HANA 2025 release notes...

v-tsaipranay
Community Support
Community Support

Hi @dpombal ,

Thank you for your question regarding data extraction options from SAP S/4HANA Cloud Private 2022 (RISE) and your upcoming transition to SAP S/4HANA 2025.

 

To integrate SAP data with Microsoft Fabric tools, you have several viable options depending on your use case. Power BI’s SAP HANA connector supports both Import and Direct Query modes, enabling interactive reporting with near real-time data access, although performance may vary based on network and SAP system load.

For large-scale, scheduled batch data processing, Azure Data Factory offers robust ETL pipelines using dedicated SAP HANA connectors, making it ideal for integrating SAP data into your data lake or fabric environment. Power BI Dataflows can be used for self-service data preparation via connectors or OData feeds but may face limitations with very large datasets.

 

Notebooks (Python or PySpark) provide flexible options for advanced analytics and custom transformations, though they require appropriate SAP connectivity setup and development effort. It is important to review SAP’s release notes for the 2025 version to understand any changes in APIs or connectivity that could impact access.

For detailed technical guidance on Azure Data Factory’s SAP HANA connector, you can refer to the official Microsoft documentation here: https://learn.microsoft.com/en-us/fabric/data-factory/connector-sap-hana.

 

Hope this helps. Please reach out for further assistance.

If this post helps, then please consider to Accept as the solution to help the other members find it more quickly and a kudos would be appreciated.

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