If your operational (OLTP) tables are reasonably big, the recommended approach is to replicate them into ClickHouse and let ClickHouse handle the joins. This avoids cross-database joins and lets the execution be pushed fully into ClickHouse. You can use ClickPipes/PeerDB to make that super easy. https://clickhouse.com/docs/integrations/clickpipes/postgres... https://clickhouse.com/docs/integrations/clickpipes/postgres
Where pg_clickhouse fits: If you’re already using Postgres for OLTP and want to offload analytics to ClickHouse without rewriting your app, the pg_clickhouse extension helps. It lets you run OLTP and OLAP queries from Postgres, while pushing the analytical queries—and their joins—down to ClickHouse, where the replicated data lives. Going native i.e. querying ClickHouse directly for OLAP will be the most optimal and is recommended if your analytics is advanced/complex. We will be evolving pg_clickhouse over the coming months to support pushdown for more and more complex/advanced queries :)