Five years ago, in-memory analytics was an approach advocated mainly by niche vendors, like QlikTech and TIBCO Spotfire. Now in-memory has become mainstream, and some naysayers thought that QlikTech's QlikView in-memory analytics solution would soon become a "me too." They suspected that QlikTech's 2010 IPO filing just ahead of Microsoft's PowerPivot in-memory product launch was an indication that the vendor wouldn't have staying power.

Fast-forward three years, and QlikView adoption is still growing at a double-digit rate (24% in the first half of 2013), while traditional BI players are limping along with single-digit growth. Meanwhile, software heavyweights such as SAP (with its Hana in-memory database), Oracle (with Exalytics and a coming 12c In-memory Option) and Microsoft (PowerPivot and a coming Hekaton in-memory database option) have embraced in-memory technology, and not just for analytics. They're supporting -- or planning to support, in Oracle's and Microsoft's case -- in-memory transactions as well.

QlikView's in-memory engine has been part of its success, but more important has been its agile deployment capabilities and robust analytics. With the frenetic pace of business, agility now trumps a perfectly architected, broad BI solution -- the strengths that incumbent BI platform vendors usually tout.

QlikView has tried to differentiate itself with its associative search capabilities, which let business users see query results as well as related and filtered-out data with few simple clicks. I'll agree that there is a differentiator in there, but one that customers typically discover only after using the product. It's not a differentiator for which customers buy the product.

[ Learn about SAP's recent analytics release -- read SAP Steps Up Visual Analytics, Mobile BI. ]

It's a subtle product difference, agrees QlikView's CTO, Anthony Deighton, but it's one reason why QlikView deployments tend to "land and expand," he says. The idea is that customers start small with the product but then grow deployments as users start asking more sophisticated business questions.

It's a valid claim. Most customers buy QlikView for its dashboard and data-mart capabilities. But associative search is something that's difficult, if not impossible, to implement in a pure SQL because you're showing everything that relates to a business question as well as everything that has been filtered out. Imagine a doctor wanting to see which treatments have been tried with a patient, but also wanting to see which treatments have not been tried. A marketing person can see which customers have bought a particular product and which customers have not bought those products.

Answering such a question with SQL would involve a complex query of SQL INTERSECTS and subqueries, and the performance would usually be too slow. QlikView's in-memory engine delivers these analytics at the speed of thought.

QlikTech competes with the largest BI vendors, but I suspect one of its biggest competitors is data-visualization specialist Tableau Software. QlikTech CEO Lars Bjork claims he sees Tableau in fewer than 10% of the company's deals. I'm skeptical. More than half of QlikView's revenues come from Europe, but in the U.S., the greenfield BI deals I've worked over the last year have all had QlikView and Tableau on the short list. Enterprise BI customers looking for agile systems also seem to have both of these vendors on their evaluation lists -- along with newer data-discovery modules from BI platform vendors.

"Natural analytics" is QlikTech's latest attempt to disrupt BI. It's a design approach that forces BI to work the way people discover and analyze data, says Donald Farmer, QlikTech's vice president of product management. The three main ingredients of natural analytics include QlikView's associative in-memory engine, a user interface that supports workflow and collaborative capabilities that let users explore data together.

QlikView.next, the next release that will support this natural analytics concept, is slated for limited beta release this year. It won't be general available until mid-2014, which puts the release about one year behind schedule.

Executives cite two main reasons for the delay. First, QlikView.next introduces a major rearchitecting that will require migration tools and services. (Executives were quick to point out that customers do not have to migrate -- unless they want to take advantage of the new capabilities -- and also that QlikView 11, the current release, will be supported for at least three years.) Second, QlikTech acquired a small visualization company called NcomVA. Based on what was demonstrated to me, the integration of NcomVA technologies and best practices will be worth the wait. Lastly, executives said that they don't want to rush such a major new release given that the company is winning deals based on current capabilities.

QlikTech is indeed winning deals, particularly when customers lack a data warehouse. When ease of use is the main purchase criterion, Tableau Software often wins the deal. The promise is that ease of use will improve when QlikView.next is released.

There's a clear opportunity for BI to become easier and more intuitive, but it's too early to tell if natural analytics will be the disruptor QlikTech executives are hoping for.