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Seamlessly Unifying Data: Applexus Perspective on Data Integration and Management Tools

Published on 4 September 2023
Data Integration and Management Tools
Arun Nair
Arun Nair
Principal Consultant - Data Management

Arun Bhaskaran Nair has over 19 years of experience in SAP technical and functional areas. A Strong consulting professional with a Master's degree in Computer Applications, Arun has proven expertise in providing market-transforming Data Migration solutions. He has extensive work experience across various industry sectors in SAP and is an expert in contributing to a wide variety of initiatives in the areas of data usage & governance, information management, data assessment, data quality, data visualization, analytics, and big data. His unique blend of technical skills, business knowledge, and work experience with multiple cross-functional teams helps provide the right solutions for clients.

Business Objects Data Services (BODS), SAP Landscape Transformation (SLT), and SAP Smart Data Integration (SDI) are the diverse set of tools available in the SAP data integration and management landscape, with different strengths, demerits, and use cases. Organizations should finalize the appropriate tool based on their specific data integration requirements, real-time processing needs, and the diverse data sources they wish to integrate.  

Today, in this blog, we’ll do a deep dive into the different data provisioning tools such as BODS, SLT, and SDI, how well they transport data between various systems, compare how they fare on different grounds, and ultimately what makes sense for your business landscape. Let's get started!

Data Migration process

Data Migration process

Data Replication:

  • BODS is an Extract, Transform, Load (ETL) tool, which can pull data from any SAP or non-SAP system through direct extraction of data or through a flat file in your local system, or by writing queries. The scheduling capability in BODS means it is primarily designed for batch processing and cannot offer real-time data replication. In essence, BODS can be used for batch load data replication into SAP HANA.
  • SLT, as another approach for extraction of data from the SAP system and is specifically built for real-time data replication, providing near real-time data synchronization between source and target systems. In essence, SLT can be used for real-time data replication into SAP HANA - SLT divides this process into 2 steps namely the Initial Load (Full Load), and then follows it up with the replication process.  
  • SDI is capable of handling both real-time and batch data processing through built-in and custom adapters - offering flexibility in meeting diverse data integration requirements in your business landscape. It supports various kinds of data integration, namely Load or Extract, Bulk or batch Extract, and data virtualization. However, real-time data replication is not available for all data sources.   

Data Sources:

  • BODS can connect to a variety of sources and disparate systems such as legacy systems as well as traditional databases, applications, flat files, and web services.
  • SLT has always been used for connecting SAP ECC and SAP HANA. In other words, SLT is typically used for replicating data from SAP systems. However, SLT can also be used for fetching data from quite a few non-SAP systems to SAP HANA.
  • SDI supports a diverse set of data sources, including traditional databases, unstructured data sources, cloud data sources, big data platforms (Hadoop), and streaming sources. SDI comes with multiple built-in connectors to several common database types.


  • BODS can load the source data into a range of target systems, including various databases, data warehouses, applications, and flat files. It is versatile in the sense that it can integrate data into different types of repositories.
  • SLT is primarily used for loading data into SAP HANA. SLT being tailor-made for SAP HANA means its main purpose is to replicate data from both SAP and non-SAP systems to SAP HANA in real time. However, it can also be used to load data into other database targets if need be.
  • SDI only supports HANA as a target system, meaning it can only load data into SAP HANA and nowhere else. However, you cannot load the data directly through application layer.

Data Transformation:

  • BODS is capable of extensive data transformation capabilities, providing a wide range of transformation functions such as data enrichment, cleansing, and integration options. In fact, out of the three, BODS can provide the best data quality and data integration transformation capabilities.
  • SLT offers minimal data transformation capabilities. It focuses primarily on real-time data replication/synchronization from source systems to SAP HANA or other databases. In essence, it mainly replicates data as-is without any significant data transformation. However, it does offer some data and structure transformation capabilities. SLT provides data transformation, conversion, and filtering capability, enabling data manipulation before loading it to a HANA database. However, you would require ABAP code to achieve significant transformations.
  • SDI provides limited data transformation capabilities that aren’t as robust as BODS and primarily focuses on advanced data processing and integration scenarios. SDI's data transformation capabilities can be achieved using different data processing engines such as data pipelines, data flows, and ML models.

Data Quality:

Data Quality

Ensuring Quality Data

  • BODS offers robust data quality functionalities such as data profiling, data cleansing, and data enrichment capabilities. Furthermore, it allows users to define and implement data quality rules to ensure data accuracy and consistency during data integration.
  • SLT is designed for real-time data replication and doesn’t offer any data quality features. It only focuses on replicating data from source systems to SAP HANA.
  • SDI doesn’t provide any dedicated data quality features like data profiling or cleansing. It is primarily focused on real-time data integration, streaming data processing, and complex event processing. SAP HANA Smart Data Quality (SDQ) is a subclass of certain SDI transformations and includes data cleansing and geospatial data enrichment.


  • SAP BODS allows easy job scheduling and monitoring through built-in job scheduling capabilities that allow users to schedule data integration workflows and other repetitive & mundane tasks at specific times or intervals using variables without the need to recreate the entire job. BODS allows users to set up recurring schedules at specific time intervals, daily, weekly, or monthly. Users can also trigger jobs based on events or external triggers or define schedules for data extraction, transformation, and loading processes within BODS itself.
  • SLT, as an ETL tool allows you to schedule data from the SAP source system or non-SAP System into SAP HANA Database. SAP SLT can be set up for scheduled data replication. Instead of selecting the real-time option, you can specify a time and frequency for the replication, when selecting “Schedule by Interval.” For example, every 20 minutes or every 6 hours. Furthermore, you can also specify a specific time for the replication, when selecting “Schedule by Time.” For example, 22:00:00.
  • SDI doesn’t offer native job scheduling capabilities, leading to lesser flexibility when it comes to scheduling jobs. However, users can integrate SDI jobs with external scheduling tools, which means that the scheduling capabilities may need to be managed externally through other tools or platforms.

Predictive Analysis:

  • SAP Business Objects Data Services (BODS) doesn’t have predictive capabilities. BODS is not primarily designed as a dedicated predictive analytics tool and focuses mainly on data profiling, data integration, ETL, and data quality management.
  • SAP Landscape Transformation (SLT) too doesn’t have any predictive analytics capabilities, nor does it offer any integration with 3rd Party predictive modeling tools.
  • SAP Smart Data Integration (SDI) supports predictive analysis. SDI can be used to draw meaningful insights based on predictive patterns - using ML and other algorithms. Simply, leverage the “Predictive Analysis” node to use the application function from the predictive analysis library to define the data flow and to schedule execution.


  • BODS requires you to have an additional license. BODS is a commercial product that needs to be licensed before you can start using it. Support, maintenance, and additional upgrades may lead to extra charges, so overall it could prove expensive to use.
  • When it comes to SLT, you don’t need an additional license as the SLT runtime license is included with the HANA Enterprise (integrated with HANA studio). SLT comes included as part of all the new S/4HANA editions.
  • SDI doesn’t require an additional license. The SDI functionality comes with SAP HANA.

Which tool makes Sense for your Business Landscape?

Business Landscape

SAP BODS is best for high-scale Enterprise-level data estates running complex scenarios involving powerful transformations, multiple sources, and diverse target systems. The efficient processing of extensive enterprise data is facilitated by the parallel processing and load-balancing capabilities within BODS. Furthermore, BODS supports seamless integration with SAP systems, enables multiple ways for data ingestion to SAP, supports various data transformations, data harmonization, profiling, cleansing, & data quality for accuracy, consistency, and completeness of data, and provides superior metadata management. However, it does prove costly due to the license charge.

SLT is a proven solution for simple and easy data replication and is best when no transformations are needed and only straightforward real-time replication is required from the source to the target system. BODS brings some real-time functionality but SLT is built for it outright. Furthermore, SLT supports batch loading of Enterprise data warehouses, considerably reduces the admin effort for recurrent master data updates, effectively synchronizes data between 2 or more SAP systems, and serves you best for both real-time and scheduled data transfers.

SDI is the best fit for real-time data integration and streaming data processing. SDI, despite not being a full-fledged ETL tool and taking extra effort for transformations is suitable for scenarios involving continuous and near-real-time data synchronization, along with the Migration Cockpit. It can seamlessly connect, access, and integrate data from multiple sources. However, it poses restrictions in handling very complex and large datasets. Additionally, SDI only supports data integration into SAP HANA, making it an ideal data transfer tool for S/4HANA migration. However, it doesn’t support direct load – you’d need to prepare a file, write it into a database, and then use migration cockpit to load.

Wrapping Up

In conclusion, there is no one-size-fits-all solution to which data provisioning tool is the best for your business landscape. The choice comes down to your specific requirements, the complexity of data integration tasks, the extent of data, and the target system in your organization. It's essential to analyze your unique organizational needs and align them with the capabilities of each tool to make an informed decision.

No single data provisioning tool excels in all aspects. At present, the tool landscape contains considerable amounts of ambiguity. If you need lots of complex transformations and need to connect diverse systems to each other, then it makes sense to use BODS. However, if you wish to have real-time data sync, then prefer SLT or SDI with SDI being best for smaller migrations of 8-12 months. If you still can’t figure it out, consult the Data Management experts in Applexus. We will help select the best tool to transfer all your Enterprise data from a wide range of source systems to S/4HANA.

SAP Data Intelligence Cloud (DIC) is poised to serve as a robust bedrock for all your data and analytics needs. Its comprehensive data management capabilities can not only help orchestrate all your enterprise analytics exercises but also help derive valuable insights from your disparate data sprawls in no time. Stay tuned for an upcoming blog on DIC from Michael Godette, Data Management Practice Lead at Applexus!

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