Today’s match will oppose the two VFH (Vehicle for Hire) leaders of the French market: Kapten (formerly Chauffeur Privé) vs Uber.
At weighing Uber is the heavier application with a weight of 255 MB. Its opponent Kapten is lighter with a weight of 73 MB, or 71% less.
All the lights are now turned on the fighters and the match can finally begin.
In the first part of the race which consists of measuring the impact of the launch phase of the application, it is Uber which is heading by consuming 10% less than Kapten. On the itinerary and driver research phase, Kapten (11.7 mAh) takes the advantage over Uber (11.8 mAh). To end this confrontation, we have set up two decisive rounds of observation of the rest phases of each opponent. During these periods of inactivity in the foreground and in the background, it is Kapten which is headed with a lower consumption of 7% and 3.7% compared to Uber.
The bell rings, end of the match!
The race was tight nevertheless it is Kapten which is declared victorious against the American giant Uber on a score very close to 15.4 mAh at 15.5 mAh by consuming globally 1% less energy. Let us note here that these two applications are nevertheless very energy consuming. We can decide between those two apps with the amount of data exchanged because Kapten consumes 21% less than Uber! This is the same finding with the memory consumption, where Kapten is much less consumer (-40%). Finally, if the storage space of your smartphone is precious for you, also prefer the Kapten application.
For those who like numbers
|Application||Version||Downloads||Playstore Grade||App weight (MB)||Exchanged data (KB)||Memory (MB)||Energy consumption (mAh)|
|Kapten||3.66.0||1 000 000+||4.3||73||10.4||185.4||15.4|
|Uber||4.272.10001||500 000 000+||4.2||255||13.2||309.4||15.5|
On a 1 minute usage scenario, Kapten and Uber have a consumption equivalent to a web browser app such as Google Chrome. (Source: Study Consumption of top 30 most popular mobile applications)
The measurements were carried out by our laboratory on the basis of a standardized protocol, respecting a specific user scenario (launch of the app, car ordering). The other scenarios are the launch of the application (20”), inactivity in the foreground (20”) and inactivity in the background (20”). This methodology makes it possible to estimate the embedded application complexity and its energy impact during the use phase.
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