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Overview

SAP S/4HANA is SAP’s next-generation ERP suite built on the SAP HANA in-memory database. Datazone connects to SAP S/4HANA systems through the CloudFeed HTTP connector, enabling table extraction and function module execution without requiring a direct database connection.

Connection Parameters

ParameterRequiredDescription
NameYesA unique identifier for your SAP S/4HANA source
Base URLYesThe base URL of the SAP system with the CloudFeed connector installed (e.g. https://your-s4hana-host:8080)
UsernameYesSAP username with read permissions
PasswordYesPassword for the specified user (stored encrypted)

Required Permissions

The SAP user account needs the following authorizations:
  • Read access to the tables and CDS views you intend to extract
  • Authorization to execute the CloudFeed RFC function modules

How It Works

Datazone communicates with SAP S/4HANA via the CloudFeed module, a lightweight HTTP adapter installed on the SAP system. It exposes SAP tables and function modules as REST endpoints, which Datazone calls to list tables, read schemas, and extract data. This means:
  • No direct SAP HANA database port needs to be open
  • Data flows over HTTPS
  • SAP’s own authorization model is respected

Differences from SAP HANA Source

SAP HANASAP S/4HANA
Connection typeDirect JDBC (host + port)HTTP via CloudFeed module
Use caseDirect database accessERP business data via SAP application layer
Auth modelDatabase userSAP application user
Use SAP S/4HANA when you want to extract business objects (sales orders, materials, finance documents) through the SAP application layer. Use SAP HANA when you need direct SQL access to the underlying HANA database.

Limitations

  • Maximum payload size per request: 10 MB
  • Extraction throughput depends on SAP system load and CloudFeed configuration
  • Supported versions: SAP S/4HANA 1610 and above

Next Steps

After configuring your SAP S/4HANA source:
  1. Create extracts to specify which tables or CDS views to ingest
  2. Configure scheduling for recurring extracts
  3. Integrate the source into your data pipelines
For more information about working with extracts and pipelines, refer to their respective documentation sections.