By Doug Henschen InformationWeek, July 26, 2011
... the vendor with the largest marketshare by far in advanced analytic tools is SAS, which held 35.2% of the market in 2010,
according to IDC figures. IBM with its SPSS unit held the second highest share at 16.2% while Microsoft was third with just 1.9% of the market. The also-ran commercial competitors tend to slam SAS in particular as the highest-cost provider.
At least one comparison of statistical puts the vendor's statistical package at the top of the price heap at about $6,000 per user for first year and about half that in subsequent years. That's multiples of the cost of some of the other vendors' software.
Among the score of smaller vendors that each have less than 1% of the market are startups Alpine Data Labs and Revolution Analytics , both of which are using low software prices among their competitive weapons, as they try to grab share of a market for advanced analytic tools that grew 8.7% last year, according to IDC stats.
Alpine Data Lab's starting price is $100,000 per year for 20 users for a subscription, but that's for a big-data in-database deployment that's tough to compare to the other two. Revolution says a $25,000 per-year deployment on a low-end server will comfortably support 8 to 10 years. Without sharing any of the prices quoted by others, I asked SAS for its latest entry-level pricing structure and the figures weren't as pricey as the competitors suggest. More on that below.
Founded last year, Alpine was incubated and spun out of Greenplum, the massively parallel processing (MPP) database vendor acquired by EMC last year. EMC is now among a handful of venture capital investors in the company, which entered the U.S. market in May.
The company's product is Alpine Miner, and given the company's MPP heritage, it's no surprise that the emphasis is on in-database processing. As the name suggests, this approach handles iterative modeling and scoring steps inside the database, taking advantage of MPP processing power and avoiding cumbersome and time-consuming movement of large data sets from the database off to a separate analytic server for analysis, and then copying results back to the database.