We were successfully ingesting hundreds of billions of ad serving events per day to it. It is much faster at query speed than any Postgres-based database (for instance, it may scan tens of billions of rows per second on a single node). And it scales to many nodes.
While it is possible to store monitoring data to ClickHouse, it may be non-trivial to set up. So we decided creating VictoriaMetrics [2]. It is built on design ideas from ClickHouse, so it features high performance additionally to ease of setup and operation. This is proved by publicly available case studies [3].
ClickHouse's intial release was circa 2016 IIRC. The work I was doing at NGINX predates ClickHouse's initial release by 1-2 years.
ClickHouse was certainly something we evaluated later on when we were looking at moving to a true columnar storage approach, but like most columnar systems there are trade-offs.
* Partial SQL support.
* No transactions (not ACID).
* Certain workloads are less efficient like updates and deletes, or single key look ups.
None of these are unique to ClickHouse, they are fairly well known trade-offs most columnar stores make to improve write throughput and prioritize high scaling sequential read performance. As I mentioned before, the amount of data we were ingesting never really reached the limits of even Postgres 9.4, so we didn't feel like we had to make those trade-offs...yet.
I would imagine that servicing ad events is several factors larger scale than we were dealing with.
We were successfully ingesting hundreds of billions of ad serving events per day to it. It is much faster at query speed than any Postgres-based database (for instance, it may scan tens of billions of rows per second on a single node). And it scales to many nodes.
While it is possible to store monitoring data to ClickHouse, it may be non-trivial to set up. So we decided creating VictoriaMetrics [2]. It is built on design ideas from ClickHouse, so it features high performance additionally to ease of setup and operation. This is proved by publicly available case studies [3].
[1] https://clickhouse.tech/
[2] https://github.com/VictoriaMetrics/VictoriaMetrics/
[3] https://victoriametrics.github.io/CaseStudies.html