Much focus around HANA has been on the differentiated in-memory architecture and advantages the technology has over traditional relational databases, such as provided by Oracle. In fact, significant ripple has been felt by Oracle shares as HANA has become a proxy for innovation in database that ultimately could challenge Oracle’s dominance in database. In the context of the $30B database market, HANA, in theory, has the potential to be a large business. While it is early in the product’s development, we see little evidence that HANA can live up to this excitement.
HANA’s in-memory architecture is optimized for columnar operations and thus the first application was in the analytics space, specifically as the new foundation for SAP’s Business Warehouse. Business warehouse performance was significantly improved with HANA and at this point, the majority of the >1,000 HANA customers are BW customers.
In May 2013, SAP announced availability of the Business Suite on HANA. Simply running the Business Suite on HANA does not bring clear advantages to the customers. In fact, we’ve heard some suggestions from SI partners that BS on HANA actually runs slower than BS on traditional relational database (such as Oracle).
SAP’s recent roadmap disclosures at the Feb investor day and last week at CeBIT shed more light on the details of BS on HANA roll out. SAP has begun to deliver a series of “optimizations” for BS on HANA. These optimizations are pieces of the core application that leverage the in-memory architecture of HANA to much more quickly return queries and speed up operations in the core apps.
Inputs at CeBIT suggest there could be significant value in many areas. For example, closing the quarter in half the time a company closed before helps to give feedback to the business sooner and start the out quarter planning process sooner. Integrated manufacturing planning enables a continuous process of manufacturing forecast, instead of a discrete set of operations and resulting delayed forecasting process. Lastly, retail optimizations can provide a more real-time relationship between aggregate customer purchases and stocking of store shelves, enabling adjustments on a daily vs. weekly or less frequent basis.
We understand there are 25-30 of these optimizations today, with financials being the area of most concentration and we believe many of the ~50 live BS on HANA customers are leveraging capabilities in this area. Given SAP has its largest concentration of customers, optimizations for HANA could deliver significant value and help to drive core license revenue.