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Qlik Sense vs Power BI & Tableau.
Hi @maggie50
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
and Tableau
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
https://go.qlik.com/Welcome-Home.html?utm_source=LinkedIn&utm_medium=social&utm_campaign=WelcomeHome
"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.
KR,
Cheenu
Hi @Cheenu
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.
Hi Qlik Community,
I saw the following post. Can you advise the ownership cost of Qlik Vs PBI Vs Tableau?
Following post only talks about Qlik Vs PBI.
https://www.linkedin.com/pulse/power-bi-qlik-licensing-deconstructed-compared-greg/
AD
Hi @robert99 ,
Many thanks for your response.
I found on MS blogs/website that PBI compresses 8-10x.
However, has your studies/experience/research spanned to larger file sizes?
In your article you refer to ~10,000Kb, but I would expect PBI to be smaller in file sizes on very small files (mostly due to the extra memory space Qlik takes for the "associative" aspect of the data model, which is expensive on small file sizes). The high compression ratio of Qlik only starts kicking in with bigger files sizes (e.g. 100+ Mb or even 500+Mb, to be more certain).
The reason for this is that the Qlik compression agent is extremely smart in storing duplicate values in any given field, which I doubt would be the case with other file types. So, I am truly interested in case studies of large files and comparisons on these. Anything under 100 Mb is just to small.
Also you refer to the sluggishness of PBI on "larger file sizes" in your article. Without addressing the data cloud (associative data model, symbolic representations, etc etc etc - whatever the name), how are you able to technologically compare response times across apps/platforms for your clients?
Notably, the symbolic representations/data cloud/ associative-blah-blah, is one that can be referenced by developers and users - through set analysis. Since this is faster (allows 'filtering' faster) than a standard "if-statement" in other technologies (which don't have the equivalent of the Qlik 'data cloud'), how do you show this to clients and also the related 'user experience' associated to more sluggish response times for more complex front-end objects (formulae)?
KR,
Cheenu
Hi @robert99 ,
I did a quick test RE compression ratio between Qlik and PowerBI.
I took an existing "larger" app, binary loaded it to create CSVs and then re-imported into PowerBI the 3 largest tables.
The filesizes are in the image below. The 3 big CSVs total 1.5 Gb, the PBIX is 323 Mb and the QVW is 180 Mb. As per my previous post of 15-16x actual Qlik compression and PBI's claim of 8-10x (per MS blogs), this seems to be correct - that Qlik is 50% more efficient in compression.
Is there a proprietary compression for PBI? One that might increase the current viewed compression ratio. Both the QVW and PBIX are "data only", no front-end objects.
Do you have any more experience or info/data regarding compression of "larger" applications?
Kr,
Cheenu