> Now you have "news" repeated, and to group this into buckets for rendering summary tables and such (with sub totals at each level), you need to iterate throug

> Now you have "news" repeated, and to group this into buckets for rendering summary tables and such (with sub totals at each level), you need to iterate through the flattened results and generate nested structures. This is something Elasticsearch gives you out of the box. ClickHouse has a number of optimization for solving 'visitor' problems that you describe. Assuming you just want to group in different ways an idiomatic ClickHouse solution is to construct a materialized view that aggregates counts (e.g., of unique users like uniq(user)). You can then select from the materialized view and further aggregate to have larger buckets. ClickHouse can also compute single-level totals using the WITH TOTALS modifier. If you need to have cascading sub-totals within the same listing as far as I know you'll have to compute the totals yourself. (That feature actually might be an interesting pull request since ClickHouse generates JSON output.) > Last I looked at Clickhouse, it had master/slave replication only, and if you want shards of data distributed across a cluster it's something you need to manually manage? ClickHouse replication is multi-master. The model is eventually consistent. Also, ClickHouse can automatically shard INSERTs across a cluster using distributed tables. That said, many users insert directly to local nodes because it's faster and uses fewer resources.