Hello Janujc,
We'd like to understand more about your use case. Readers of temporal charts expect time continuity, or a fixed cadence (eg. daily bin width). So, while omitting periods when no event happened sounds attractive, it's also useful for most chart readers to know when nothing happened, and if these were shorter or longer stretches, or maybe it was rare that nothing happened. The reader can easily assess it on a regular timeline. But the chart reader can no longer tell it from the shape of the chart if you cut out the zero-event days. The chart reader would be forced to read the tick labels one by one.
It'd be especially misleading (untruthful in spirit) to link adjacently placed, but non-adjacent days with a line. Also, any trend that can be read out from that would be spurious, as the zero days would be omitted. A 5 followed by 7 then 9 is not the same as 5 followed by a bunch of zeros, followed by 7 then immediately a 9.
So a regular, vertical bar chart based time histogram would be better.
It's worth discussing it with data visualization best practices in mind, and get to the bottom of the requirements before looking for a technical solution for this.
If you have few time series, then multiple bar chart histograms atop of one another would be a good alternative; clear readability as the values are seen even if there's gaps among bars for the zero days. If you have many time series, it's worth aggregating, as it'd be a mess, whether with lines or charts. Eg. max aggregation, or averages (or a chart for each, positioned underneath one another).
If there are compelling reasons for the type of ordinal time axis you seek, we'd like to learn all details we can about it, so we better understand the needs. An enhancement request with snapshots, explanation etc. would be best for this, you can create a new "Feature request" issue here: https://github.com/elastic/kibana/issues If you have a support contract, please reference this github issue to your support folks, so that we can keep track of it that way too. Worth pasting your github issue into this discussion as well, to make it discoverable by others.