I tried to use PolyScale in the past but had issues with performance because updating a row would invalidate the entire cache. I wonder if that has improved?

Yes, in the early versions of the automated invalidation, the logic cleared all cached data based on tables. That is no longer the case. The invalidations only remove the affected data from the cache, globally. You can read more here: https://docs.polyscale.ai/how-does-it-work#smart-invalidatio...

It didn't impact everything, I think I was hitting this case:

> When a query is deemed too complex to determine what specific cached data may have become invalidated, a fallback to a simple but effective table level invalidation occurs.

We've made a lot of changes - give it a try again or feel free to reach out to support@polyscale.ai and we'd be happy to assist you.

The Noria solution seems superior. It doesn't necessarily have to rerun queries from scratch because a single row changed.

One might argue one approach is superior over the other, I'd argue they are more like duals of one another. The PolyScale approach analyzes the queries and identifies the semantic and the statistical relationships between reads and writes. The Noria approach forgoes analyzing the queries and instead maintains a materialized view like representation of where the data should-be-at-now.

The PolyScale approach does not maintain / require a separate data representation and so saves space, but on the other hand, precisely identifying the relationship between reads and writes is not possible and so the PolyScale approach must sometimes over-invalidate in the interest of accuracy.

There are scenarios in which show-me-the-data (Noria) beats show-me-the-math (PolyScale), for example, running complex queries against a relatively simple schema. There are also scenarios in which the statistical (PolyScale) approach wins, for example if the queries are relatively simple or if not all writes to the underlying data are visible.

There are additional unique features of PolyScale that set it apart. Full disclosure, I work at PolyScale.