Filtering by partial string match on dimensions. It is equally slow on both of them.
For straightforward filters and aggregations, yeah, Clickhouse is faster. However I read a PR by the Druid team where they added a vector engine. If they release that, then the performance gap should be smaller or maybe in Druid’s favor depending on the dataset.
You are right about insertions up to a point.
If you consider data loads as insertions, with Druid I could scale my cluster elastically to speed them up. With Clickhouse I am bound by the query nodes.
Also, Druid can ingest data in real time using a special type of node that wasn’t part of the original distribution. I haven’t done real time data ingestion on Clickhouse. Hourly updates are good enough for my use case.
For straightforward filters and aggregations, yeah, Clickhouse is faster. However I read a PR by the Druid team where they added a vector engine. If they release that, then the performance gap should be smaller or maybe in Druid’s favor depending on the dataset.
You are right about insertions up to a point.
If you consider data loads as insertions, with Druid I could scale my cluster elastically to speed them up. With Clickhouse I am bound by the query nodes.
Also, Druid can ingest data in real time using a special type of node that wasn’t part of the original distribution. I haven’t done real time data ingestion on Clickhouse. Hourly updates are good enough for my use case.