We use the concept of 'topics'. A topic encodes: 'The part of the index a query cares about'.

For example, given a query like "fetch user where id = 1", there could be a topic like "users:id:1" [1]

When a WAL record comes in, we find queries by their topics, and invalidate them. This triggers a refresh.

This is inspired by Figma's LiveGraph [2], which in turn is inspired by Asana's Luna [3]. The essays cover the idea in more detail, but you can also start diving into the code, at invalidator.clj [4]

[1] This is an example. Inside Instant, we encode them as a 'datalog' pattern. Something like `[:ea "1" :users/id]` [2] https://blog.asana.com/2020/09/worldstore-distributed-cachin... [3] https://www.figma.com/blog/livegraph-real-time-data-fetching... [4] https://github.com/instantdb/instant/blob/main/server/src/in...