Qlik Sense documentation and resources.
Qlik Sense vs Power BI & Tableau.
The report has been keep up to date. Although I haven't incorporated this very recent change from Tableau
There is also this to consider as well. These Qlik articles were done fairly recently
Ops. The latest Tableau update
I plan to update this report soon.
But here's a cost comparison that has been done by Qlik. It shows that the PBI costs can increase quickly once a user moves to Premium (2-3 times the price of QS for 50 users).
PBI plan to move to a Premium Per User (PPU) licensing model soon. But the price per user has not been announced yet.
"We are also very excited to announce Premium Per User – which provides capabilities of Power BI Premium, now on a per-user license model as a new option for customers. This addresses a key customer and community ask – to provide a lower cost entry price point to get access to Premium capabilities. Premium Per User will be available at no cost during public preview. Premium per user will be uniquely affordable and highly competitive among individual user offerings in the industry. Stay tuned for the official pricing announcement as we get closer to the GA timeframe. I guarantee you won’t want to miss it."
Qlik's (excellent) Welcome Home compares Qlik Sense to PBI
"Users are telling us they keep coming back to Qlik for three main reasons: performance, usability and price."
I've been following this thread on LinkedIn. Where a Tableau author is learning Qlik.
One challenge was to recreate a chart type in Qlik. Christophe Brault took up the challenge
Interesting and comprehensive comparison of the front-end and the platforms as visualisation tools.
However, I always had the impression that the "Qlik difference" was hidden under the hood and hard to explain to technical/semi-technical individuals without being able to explicitly show it to them.
The data compression is also something else that does not seem to be in the picture when talking about the different platforms. Considering Qlik's marketed 10x compression (my observation seem to show that this is conservative and more to the tune of 15-16x on average), wouldn't it be correct to say (ballpark figures) that if PBI has a limit of 1GB filesize, the equivalent would be a 100Mb Qlik file? The whole compression perspective seems to be disregarded when comparing "like-for-like", therefore always resulting in "small" data comparisons across platforms.
In my past as a consultant, I had created a demo to try and portray the Qlik USP: the "data cloud" as Hakan Wolge referred to or which is now, I guess the associative data model. This is also what set analysis is impinged upon: a coding language to leverage this "data cloud" (the "invisible" symbolical representations table).
Does this 1-minute video I have created make sense to more programming-orientated Qlik developers than myself, or am I completely "off-the-ball"?
Look forward to your thoughts.
In reply to your post
Considering Qlik's marketed 10x compression (my observation seem to show that this is conservative and more to the tune of 15-16x on average), wouldn't it be correct to say (ballpark figures) that if PBI has a limit of 1GB filesize, the equivalent would be a 100Mb Qlik file?
The saved file size for the comparison I did was slightly less for PBI. So I would say PBI compression is also VG.
However, I always had the impression that the "Qlik difference" was hidden under the hood and hard to explain
The key difference for what I was looking for was
The associative data model
I don't try to explain this now to new users or potential buyers.