Pivotal is going after enterprise incumbents by rejigging its own pricing scheme to make buying its technology simpler for its customers.
The revamped pricing scheme was announced on Wednesday and will see Pivotal license the software within its portfolio on a flat per-CPU pricing model as long as customers buy capacity for two to three years.
The software covered by this "Big Data Suite" includes Pivotal Greenplum Database, GemFire, SQLFire, GemFire XD, HAWQ, and Pivotal HD. It will also include support and maintenance for all the packages as well.
This means that a customer could buy, say, 2,000 cores worth of Pivotal software for two years and use the majority of this on servers dedicated to its Pivotal Greenplum Database, but over the years migrate its data over to the Hadoop-based "PivotalHD" solution, and also set aside some cores for "HAWQ" analysis without having to pay anything extra as long as it didn't use more cores.
If this sounds remarkably sensible, that's because it is. Typical enterprise pricing schemes don't make it nearly so easy for clients to swap out one software package for another, and the licensing models of incumbents like Oracle and IBM are known to cause more headaches than hallelujahs among CIOs the world over.
It's because of this flaw (and not as the associated Pivotal marketing would like you to believe, altruism) that Pivotal has revamped its pricing.
"We are putting a lot of price pressure and complexity pressure on the traditional database vendors, whether Oracle or a Teradata or an IBM," Pivotal's veep of data platform product management Josh Klahr told The Register.
Pivotal would not, despite repeated questions, disclose the exact per-core pricing of its new scheme. "What I can say is we have priced it to be much more competitive with the pricing expectations set by the Hadoop ecosystem than the traditional in-memory or column store customers," Klahr said.
Pivotal will not levy a fee for the amount of data either stored within its suite, or in-memory, avoiding a potentially lucrative tax on organizations dallying with 'big data' applications, Klahr said. This may help it avoid causing customer discontent as VMware did with its abortive so-called 'RAM tax' back in 2012.
"We should not penalize customers for storing data on HDFS," Klahr explained.
Another side effect of the pricing is that Pivotal's salespeople now have a very clear number in their heads around which to assemble deals and discounts which may reduce those nasty occurrences where promises on price are made but not kept.
We asked Klahr how he would have reacted to this type of pricing several years ago when he worked within technology.
"Five years ago I was working inside the data group at Yahoo and I think I would have said 'you're dreaming, it sounds great but that's not how it works'," he said. "We were dealing with Oracle, with Microstrategy, we had our own internal Hadoop distribution. If it had happened while I was there I would have thought it was great." ®