SAP HANA: the Ferrari of a datastore.
March 07, 2019

SAP HANA: the Ferrari of a datastore.

Dhruba Jyoti Nag | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with SAP HANA

SAP HANA is used by my organization to support a new analytics platform being developed for real-time analysis of product consumption. Based on product consumption, pricing adjustments are made in real time. SAP HANA is not used as a mere data store. Rather its analytical engines led to its adoption in our project.
  • Advanced analytical engine
  • Real-time analytics
  • Numerous engines, like spatial engines, which help with modeling.
  • SAP HANA is not for traditional data operations.
  • It is costly while on-premise, the licenses are not cheap.
  • It is a new software with limited adoption and there are fewer resources who have working knowledge.
  • SAP HANA is not for everybody. It is for high-end analytical apps and when used properly, the ROI is huge. E.G., it is ideal for creating a correlation between a pricing engine and an inventory. The price of commodities can be manipulated in real-time based on demand.
  • It is not a traditional data store. So if it is used to store data, it is just a royal waste of precious resources.
  • It is ideal for creating models based on real-time data and, hence, it can provide good ROI for businesses which rely on data for marketing.
There are many alternatives to SAP HANA if we consider functionality. Most of them, just like HANA, have their own niche place of specialization. But SAP HANA is at the forefront when it comes to performance comparison in its area of expertise which is business intelligence and real-time data analytics. It is super fast thanks to the ground up optimization and design which SAP did.
It is a super fast data platform. SAP has gone all out with these, which they could not have done if they assembled other technologies and created a solution. Instead, they went ahead and designed it with performance in mind. Hence, it is blazing fast, and because of massive parallelization, it can process an amazing amount of data in mere seconds.