Quentin Clark - Structure 2015 - theCUBE - #structureconf
Channel: SiliconANGLE theCUBE
Date: 2015-11-18

How SAP helped streamline modern database response time | #StructureConf
by Tim Hawkins | Nov 19, 2015

Decades ago, in-memory databases were divided into two distinct components: transactional databases and analytic databases. This was done because, in terms of response time, the analytic databases began to seriously outpace their transactional counterparts. However, because of SAP SE’s HANA database management system, analytic and transactional databases are being reunified, because HANA allows them to function together in real-time, according to Quentin Clark, chief business officer at SAP.
Clark spoke to George Gilbert, Wikibon’s Big Data analyst and cohost of theCUBE, from the SiliconANGLE Media team, during Structure 2015 in San Francisco.

SAP S/4HANA and new features in supply management

Although transitional and analytic databases have been reunified, other issues, such as duplicate data and certain user inputs, have meant that newer reunified databases do not always function in real-time.

“This month we released this version of S/4HANA that supports all our logistics, manufacturing, supply management, that functionality, in addition to finance,” Clark said. “And in that space, (with) the supply optimization that can be done, with the prediction capabilities that are in HANA, in that integrated hole between what has happened, and what is currently going on, has produced new features in supply management.”

Database pricing: Traditional vs. logical tier

As modern data capture volumes change compared to past levels, traditional database pricing is seen by some as excessive, Clark explained. Logical tier pricing is an option, although some companies are unsure about this approach because it would require changes in how applications treat the data.

“The HANA system, because it’s married together the transactional/analytic side, is allowing us to build our applications with new value,” said Clark, “and leveraging the in-memory data structures and leveraging the in-memories per revolution if you will … to achieve that, the value is there. And customers will always pay for the great value.”

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