Disclaimer: This is a side project, not a production story. The slow-query problem is real, but the database is synthetic data I generated to make it show up on demand. I have no connection to PgCache. Everything here is in a repo you can clone and run. I tested version 0.6.2.
A handful of dashboard queries on one of my projects were fine for a year and then weren't: count users by tier, revenue grouped by country, best-selling products per category. Nothing exotic, just aggregates and joins over tables that had gotten big.
The usual fixes didn't sit right with me. A materialized view means picking a refresh interval and serving slightly stale numbers in between. Redis in front of Postgres means writing and maintaining code that knows which cache entries to throw away on every write. A read replica just runs the same slow query on another machine.
PgCache offers a different trade. It's a proxy that talks the Postgres wire protocol, so your app connects to it as if it were the database. It caches reads. And instead of expiring entries on a timer, it follows Postgres's replication stream and refreshes a cached result when the rows behind it change. That stream is the same feed Postgres uses to copy data to a standby server , a running log of every insert, update, and delete.
