According to SAS’ press release,
SAP and SAS will partner closely to create a joint technology and product roadmap designed to leverage the SAP HANA® platform and SAS analytics capabilities. By incorporating the in-memory SAP HANA platform into SAS applications and enabling SAS’ industry-proven advanced analytics algorithms to run on SAP HANA, decision makers will have the opportunity to leverage the value of real-time data analysis within their existing SAS and SAP HANA environments.
SAS and SAP plan to execute a co-sell pilot program to engage select joint customers to validate SAS applications running on SAP HANA. The goal of this program is to build and prioritize the two firms’ joint technology throughout 2014, in particular for industries such as financial services, telecommunications, retail, consumer products and manufacturing. The applications are expected to target business areas that require a combination of advanced analytics running on an in-memory platform that will be designed to yield high value results. Such opportunities exist in customer intelligence, risk management, asset management and anti-money laundering, among others.
How soon we forget; just six months ago, SAS leadership trashed SAP HANA from the stage at SAS Global Forum.
SAS and SAP share a commitment to in-memory computing, but they have a fundamentally different approach to the technology. SAP HANA is a standards-based persistent in-memory database, with a strong vendor ecosystem. SAS on the other hand, builds its in-memory analytics on a proprietary architecture, and has a vendor ecosystem of one. HANA succeeds because it is an easy decision for SAP-centric companies to adopt the product for small high-concurrency databases with one data source. Meanwhile, even the most loyal SAS customers choke at the TCO of SAS High Performance Analytics.
In-memory databases make economic sense when (a) you don’t have much data, and (b) usage is read-only, (c) users want small random packets of data, and (d) there are lots of users. The NBA’s statistics website (powered by SAP HANA) is a perfect example: less than a terabyte of data, but up to 20,000 concurrent users seeking information about how many free throws Hal Greer hit in 1968 against the Celtics. That’s a great application for BI tools, but not for high-end predictive analytics. SAP’s HANA Predictive Analytics Library may be toylike, but it’s likely good enough for that use case.
SAS Visual Analytics makes more sense coupled to an in-memory database like HANA than to its existing LASR Server architecture. It doesn’t do anything that can’t be done in Business Objects, but there are likely a few customers in the market who are both SAS-centric and have an all-SAP back end.