SAP’s Roadmap for our Data Warehouse Portfolio

Posted by Prakash Darji on August 24, 2012

SVP & GM, Platform As A Service

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Recently, a lot of folks have been asking about where to find SAP’s Roadmaps for HANA and our Data Warehouse portfolio.

Firstly, all roadmaps for SAP are available on service marketplace at This site is available to all customers and partners that have access to our software via their service marketplace logon. This site is restricted to customers and partners for legal reasons.

The direct links to the roadaps are available below:

However, there has been a lot of debate in the community around using HANA vs BW on HANA. Firstly, Steve has written a blog called “Does HANA Replace BW – Part 1“. Then Jon Appleby weighed in with “Does HANA replace BW – Part 2“. Sven Jensen then wrote two blogs about BW on HANA: BW as an Enterprise Data Warehouse as well as Building the Business Case for BW on HANA.

Now as you look at these blogs, you’ll see that there’s a lot of debate of whether HANA will replace BW and what people should do. This blog as well as the associated document below describes where we’re going with Data Warehousing.

Fundamentally, BW is a management framework to manage data. Companies can build point data marts. Now the world has largely evolved from just Enterprise BI to supporting other Analytical Use Cases such as Adhoc Analysis, Self Service BI, Operational Analytics, Real-time Analytics, Social Media Analytics, or Big Data Analytics. Even including analytical use cases that are driven by governance and logs, such as Query-able Archive Analytics.

As these analytical capabilities evolve, we find that the best place to store “High Value” Analytical data is HANA. However, as you have multiple data-marts, you will typically evolve to requiring a Data Warehouse approach. Fundamentally, a data warehouse is a methodology to manage multiple data marts. Common types of data warehouses include a “Central Data Warehouse” or a “Logical Data Warehouse”. Each approach has benefits, and BW today, a central data warehouse that provides capabilities to manage multiple types of datamarts, and HANA fundamentally broadens the types of data marts you could support as it evolves to the Real-Time Data Platform, as new types of analytics are driven by new types of data (events, signals, etc…). For examples of new types of data driving analytics today, see Steve’s blog entitled “Beyond the Balance Sheet: Run Your Business on New Signals in the Age of Big Data“.

As SAP has created a Centralized Data Warehouse approach with SAP BW, that is not the only type of Data Warehouse capability a customer may want, and SAP also supports custom building data warehouses for customers who don’t prescribe to the framework we’ve provided with BW.

The following document addresses SAP’s approach and strategic direction in Data Warehousing. First, starting with the types of data marts our platform is evolving to support, followed by the challenges of point data marts and the advantages of adopting a Centralized or Logical Data Warehouse. SAP’s strategy is to allow customer choice whether the customer wants to adopt BW as their Data Warehouse or whether customers want to build their own.

Finally, SAP is evolving the point technology to the “Real-Time Data Platform” as a single platform for running BW or Custom Building Warehouses.

See this document for details on the strategic direction for data warehousing at SAP.

For details on the roadmap for each product, see service marketplace here:

I imagine the debate will continue as there are always folks that believe one product or approach is superior than another. Usually, this comes from background and familiarity with a particular product or approach. In order to meet customer requirements, SAP’s strategy is open to customer choice for Buying BW on HANA or leveraging the Real-Time Data Platform to Build your own warehouse. Either way, I imagine the debate will continue. This is largely because customer requirements will dictate the approach that is required to meet the needs.



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