The title seems to be quite provocating since both solution actually have strong partisans in both side.
When you work in the data analysis field and data visualization, debates are frequent for analysts when it comes to defend which is the best solution. Analysts tend to have their own habits, sticking to the same tool for the last couple of years, and really, no one enjoy change. Change is scarying – hence the both side of it.
Qlikview is a really nice tool when it comes to data manipulation and data preparation before building a visualization. Qlikview embeds a scripting engine which basically allows every advanced users to create variables, build loops, write data into files, connect dynamically and use IF … THEN … clauses. Not like a real programming language but pretty much like it. If I had to compare, I would say that this scripting interface is really looking like a very very very easy Python or Ruby.
Qlikview is also good when it comes to handle huge datasets. Qlikview develops his own data format set: .qvd and .qvx. What’s the difference? Not much exception the compression. Far more advanced than pure .csv files but especially designed to fit Qlikview data’s handling engine.
When it comes to lean user interface and graphics , then Tableau seems to have a far better interface compared to Tableau. Maybe one of the reasons why Qlikview launched at some point QlikSense, one of his massive investment if we consider that their roadmap is clearly focused on improving this new data visualization product.
Tableau Software provides to the end user a clean and modern user interface and to the developer a multitude of visualization possibilities, easy to implement. If Tableau accepts a multitude of data sources, it seems that the scripting interface is quite limited. In terms of visualization, graphics, data injection, data crossing, colors, graph type, Tableau is undoubtedly a great tool, maybe less geeky and still quite powerful.
Other aspects should be considered also when it comes to pricing, licensing and IT architecture.
Both data visualization softwares have one major default: they only exist on Windows plateform, not on Linux, major default when we know that most of the companies have implemented a Linux-based architecture.
In terms of pricing, don’t expect cheap solution when it comes to scale the product internally in the company. Good products have a price – but the pricing grid are fairly adapted to the size of companies.