The core storage engine borrows heavily from it - I'll attempt to summarize and apologies for any errors, it's been a while since I worked with VictoriaMetrics or ClickHouse.

Basically data is stored in sorted "runs". Appending is cheap because you just create a new run. You have a background "merge" operation that coalesces runs into larger runs periodically, amortizing write costs. Reads are very efficient as long as you're doing range queries (very likely on a time-series database) as you need only linearly scan the portion of each run that contains your time range.