Use SAP HANA-Optimized InfoCubes and DSOs for Faster Data Access

  • by Prakash Darji, Vice President and General Manager, Data Warehousing Solutions and SAP HANA Platform, SAP
  • Daniel Rutschmann, Director, Data Warehousing Solutions and SAP HANA Platform
  • May 11, 2012
Gain an understanding of how to use the new InfoProvider types introduced with SAP NetWeaver BW on SAP HANA, such as SAP HANA-optimized InfoCubes and DataStore Objects. Learn when and how to use them to take full advantage of the in-memory computing capabilities within SAP NetWeaver BW on SAP HANA. Doing so enables your organization to dramatically shorten the time it takes to load data and provide required information for reporting.
Key Concept

SAP NetWeaver BW on SAP HANA introduces new InfoProvider types that are optimized for the use of in-memory computing capabilities. As companies deploy SAP NetWeaver BW on top of SAP HANA, there are significant improvements in the area of data modeling that enable them to implement a much leaner Layered, Scalable Architecture. This approach results in a shorter time-to-market of developments of new applications and data models with SAP NetWeaver BW. Additionally, data loading cycles are shortened. 

Traditionally business systems are deployed in a three-tier, client-server architecture in which the end users access applications on their desktop clients. With SAP NetWeaver BW, the data for these applications resides within various database management systems. The heavy workload of extracting, harmonizing, integrating, and consolidating data — thus transforming it into valuable information — occurs in the application tier. With SAP NetWeaver BW-based business solutions, the application layer typically consists of several ABAP application servers.

The database layer usually becomes a bottleneck as there is a lot of data traffic between the application and database layers caused by frequent data reads from the database into the application layer. With SAP HANA, this dramatically changes.

With the technology and software behind SAP HANA, application logic can be executed in the in-memory database layer with incredible speed, decreasing the need of transferring large data sets back and forth between the database and application servers. Multi-core CPUs combined with massively parallel processing (MPP), in-memory, and columnar constructs enable data-intense operations to occur close to where the data is stored. For example, by moving DataStore Object (DSO) activation runtime from the application layer to the database layer, the processing time is improved on average by a factor of 10 to 15.

Figure 1 outlines the move of application runtime to the in-memory database layer.

Prakash Darji

Prakash Darji is an experienced professional with more than 10 years of end-to-end experience in enterprise software. He has a broad depth of experience including corporate strategy, sales, product management, architecture, and development. He has experience in product launch activities, including positioning, packaging, and pricing. He has delivered numerous product releases in a variety of capacities through his career. He thrives on building high-performing, scalable teams to achieve strategic deliverables, whether they close strategic sales deals, roll in product features, or roll out new releases. He is a recurring author for several publications and a speaker at SAP conferences around the world. Prakash is on LinkedIn at

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Daniel Rutschmann

Daniel Rutschmann has been with SAP for more than 11 years, with a strong focus on enterprise data warehousing throughout his entire career, especially in the area of SAP NetWeaver BW. He has held different roles within SAP Consulting over several years, building a strong relationship with customers from various industries around the globe. His expertise is based on many years of consistently delivering successful solutions and IT architectures. Today, he is director for SAP NetWeaver BW on SAP HANA and part of the solution management team for data warehousing solutions and the SAP HANA platform.

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