As an example, we have a pipeline of services. I can compute the time spent in each service with multiple levels of percentiles and group that data by high cardinality fields (as in, hundreds of thousands or more values). I just did a search for 4 hours of data across thousands of nodes for half a dozen or so services with multiple eval statements all piped to a timechart doing over a dozen stats operations. Half a billion events. It got done in under a minute.
Splunk charges so much because they are just so dang powerful.
In the early days Splunk pricing was exorbitant (we evaluated Splunk 7 years ago and dismissed it), but licensing has changed in recent years and it is now priced by volume ingested (the pricing is transparent and listed on their website now). At low volumes, the pricing is similar to Sumologic, and is pretty accessible now to smaller dev shops. Open-source collectors like fluentd also help to intelligently reduce the ingest volume.
At high volumes, the TCO changes quite a bit.