How to read a value-quantile diagram? I've been reading an article on ACM queue, and got confused by figure 6 (latency distribution of a push-only workload), where the authors used the y axis to display the latency, and the x axis to denote the quantile. 

The problem is, I really don't get how to read that plot: 


*

*What do the bars show? How can interpret a long bar at 0.95, for instance?

*Where do I find, e.g. the mean?


By the way, what is the name of this type of plots?
 A: It is a chart of quantiles, in effect the inverse of the cumulative distribution function.
The style is similar to a waterfall chart, which I suspect is not quite appropriate here: blocks which are separated horizontally as shown here suggests to me that certain cumulative probabilities do not exist, but blocks which are not separated vertically suggests to me that all latencies do exist.  I am not certain that makes sense. 
You can estimate the medians instantly by taking the values when the cumulative probability is $0.5$.  
The means would be the areas under the curves, if the data were presented as curves rather than separated blocks.  You would need the curve to reach, or to be arbitrarily close to, the right hand side (a cumulative probability of $1$) to calculate the mean.
The long bar at a cumulative probability of $0.95$ suggests to me that there is a 2.5% chance the latency is between about $7200$ and about $10200$, as there are about $40$ bars for each variable.  There is also a chance it is above $10200$, possibly very much above.   
