SAP Landscape Transformation Replication Server (SLT) provides real time data replication from SAP and non SAP Sources. SAP LT Replication Server does not have to be a separate SAP system and can run on any SAP system with SAP NetWeaver 7.02 ABAP stack. There are different methods available for data replication from a source system to a HANA database. The data replication is done differently in each of these methods.
- Trigger Based Data Replication
- Extract, transform, load (ETL) based data replication
- Transaction Log Based Data Replication
a) Trigger Based Data Replication
The Trigger Based Data Replication using SAP Landscape Transformation Replication Server is based on capturing database changes via a trigger base recording mechanism in the connected SAP and/or non SAP source systems. This method of replication benefits from being database independent, and also can parallelize database changes on multiple tables or by segmenting large table changes. This allows real time and scheduled, data replication, only replicating the relevant data into HANA. It also provides the ability to migrate data into HANA format while replicating data in real-time. The set up of SAP LT Replication Server is simple and fast which can be done in a day and is fully integrated with HANA Studio.
b) Extract, transform, load (ETL) based data replication
Extract, transform, load (ETL) based data replication uses SAP Business Objects Data Services to extract the relevant business data from a source system such as ERP and load it into a HANA database. In addition, the ETL based method offers options for the integration of third-party data providers. Replication jobs and data flow are configured in Data Services. This permits the use of multiple data sources including external ones and data validation.
c) Transaction Log Based Data Replication
Transaction Log Based Data Replication using Sybase Replication is based on capturing table changes from low level database log files. This method is database dependent. Database changes are propagated for each database transaction, and they are then replayed on the HANA database. This maintains consistency, but can not use parallelizing to propagate changes.