I just wonder if ClickHouse can be used for storing time-series data in the case like this: schema with columns: "some_entity_id", "timestamp", "metric1", "metric2", "metric3", ..., "metricN". Where each new column containing metric name can be added to the table dynamically, while adding entry with this metric name.
Have not found any information about dynamical table extend in official documentation.
So can this case be implemented in Clickhouse?
UPD: After some benchmarks we found out that ClickHouse writes new data faster than our current time-series storage, but reads data much more slower.
It would probably be better to modify your schema to have 4 columns:
"some_entity_id", "timestamp", "metric_name", "metric_value"
You can include "metric_name" in the MergeTree index, to improve performance when searching for a specific metric of an entity. Test with and without it, to see if it's useful for the kind of queries you make.