When SAS released its new in-memory analytic software last December, I predicted that SAS would have one reference customer in 2012. I believed at the time that several factors, including pricing, inability to run most existing SAS programs and SAS’ track record with new products would prevent widespread adoption, but that SAS would do whatever it takes to get at least one customer up and running on the product.
It may surprise you to learn that SAS does not already have a number of public references for the product. SAS uses the term ‘High Performance Analytics’ in two ways: as the name for its new high-end in-memory analytics software, and to refer to an entire category of products, both new and existing. Hence, it’s important to read SAS’ customer success stories carefully; for example, SAS cites CSI-Piemonte as a reference for in-memory analytics, but the text of the story indicates the customer has selected SAS Grid Manager, a mature product.
Recently, a United Health Group executive spoke at SAS’ Analytics 2012 conference and publicly endorsed the High Performance Analytics product; a search through SAS press releases and blog postings appears to show that this is the first genuine public endorsement. You can read the story here.
Several comments:
– While it appears the POC succeeded, the story does not say that United Healthcare has licensed SAS HPA for production.
– The executive interviewed in the article appears to be unaware of alternative technologies, some of which are already owned and used by his employer.
– The use case described in the article is not particularly challenging. Four million rows of data was a large data set ten years ago; today we work with data sets that are orders of magnitude larger than that.
– The reported load rate of 9.2 TB is good, but not better than what can be achieved with competing products. The story does not state whether this rate measure load from raw data to Greenplum or from Greenplum into SAS HPA’s memory.
– Performance for parsing unstructured data — “millions of rows of text data in a few minutes” — is not compelling compared to alternatives.
The money quote in this story: “this Big Data analytics stuff is expensive…” That statement is certainly true of SAS High Performance Analytics, but not necessarily so for alternatives. Due to the high cost of this software, the executive in the story does not believe SAS HPA can be deployed broadly as an architecture, but must be implemented in a silo that will require users to move data around.
That path doesn’t lead to the Analytic Enterprise.
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