It was back in April at Qonnections, our 10th global partner conference that we unveiled Qlik Sense 2.0 and shared our platform strategy with the world. It was also the first time we talked in detail about our plans for QlikView 12. Today I’m delighted to be able to share the news that it’s arrived! QlikView 12 will you please stand up and show yourself to the world!
There is no doubt that this is an eagerly awaited release by many of our 37,000 strong global customer base. But why? QlikView is a very mature product, it's functionally rich, and it’s undoubtedly in my opinion the product that revolutionized business intelligence and ultimately created the global data discovery market as we know it today. So what is so important about QlikView 12?
An investment in QlikView 12 is an investment in Qlik
With QlikView 12, Qlik delivers on its commitment to its proven, market-leading data discovery solution which secures our customers long term investment in the product. It also lays the foundation for our customers to partner with Qlik to build out their business intelligence strategies and meet the expanding needs of their BI consumers by addressing multiple use cases through a unique platform approach to visual analytics.
QlikView 12 now runs on the second generation QIX (Qlik Data Indexing) engine that powers the entire Qlik portfolio. With this improvement, we can more easily help customers address new use cases in Qlik Sense by allowing them to share data models across the platform.
Our investments also benefit the way our customers use QlikView today. QlikView 12 delivers a number of deployment, performance, security and connectivity enhancements along with greater accessibility through enhanced mobile touch-enabled capabilities. In addition QlikView customers will be able to now take advantage of Qlik’s strategy to deliver value added cloud services – such as Qlik’s “Data as a Service” offering, Qlik DataMarket.
(If you want to see some of this in action check out this brief presentation)
QlikView 12 - What's New Presentation
QlikView - REST Connector
QlikView - Qlik Data Market
Put simply, QlikView is a business intelligence solution with an unrivaled pedigree, functional richness and delivers the lowest cost of ownership in the market. Many customers have already delivered robust guided analytics and dashboards to knowledge workers across their organizations, and with QlikView 12, that investment is secured.
Hi Raj - the QIX engine is the new term to describe - the Qlik Indexing Engine which is the core in-memory component that provides on-the-fly aggregations, compresses the data and stored and indexes the dimensional values that increases analysis performance. Overall the same experience is still achieved with the way it worked previously, including the associative experience.
Apart from a number of bug fixes and optimizations, the major improvement is our change from: Row-based storage to Columnar. The old Qlik engine (QlikView 11) has row based internal data tables, whereas the new QIX engine (Qlik Sense + QlikView 12) has columnar data tables. This change provides performance improvements, a modern storage design and data model compatibility between QlikView and Qlik Sense. For example, any data models stored in the form of .qvd files, whether created by Qlik Sense or QlikView - will work with both products.
Hi Jonas - et al - We will have a quick review of this and also update you on our findings. Initial reports have shown an increase in performance, but your feedback is very valuable and we appreciate you taking the time to perform these tests. I will update you all shortly.
I did my own testing yesterday on my new laptop. I used Open HWEtest_parallel_1G.qvw app that Qlik Scalability folks normally use for application testing with JMeter (it has 1 billion rows) and I also used our most intensive app I could find (nice star schema design with 64 Million rows). First app uses very simple straight expression like SUM and COUNT. Second app uses everything - complex set analysis, AGGR etc.
In both cases performance was very similar. I repeated all tests 4-5 times:
Hello Boris an etl al - I have received the following updated information in regards to the performance improvements.
The performance improvements will vary by application and not every application will see improvements. Generally you will need to add more columns to an data model to see more improvements or if you are using a data model that is joined by association.
The performance improvements are in 2 areas:
Wider fact tables. It is impossible to state a fix number of columns where QV12 is faster than QV11, but adding columns will show where the breakpoint is.
Shared file caching, gives improved response times in QVS clusters, especially in ramp-up scenarios where large number of sessions are started in a short time-period.
