I wrote a book on PostGIS and used it for years and these single node analytical tools make sense when PostGIS performance starts to break down. For many tasks PostGIS works great, but again you are limited by the fact that your tables have to live in the DB and can only scale as much as the computing resources you have allocated.

In terms of number of functions PostGIS is still the leader, but for analytical functions (spatial relationships, distances, etc) having those in place in these systems is important. DuckDB started this but this has a spatial focused engine. You can use the two together, PostGIS for transactional processing and queries, and then SedonaDB for processing and data prep.

A combination of tools makes a lot of sense here especially as the data starts to grow.

I think this is a great perspective in my professional experience it was very common to be using multiple tools. ESRI for some things, GDAL for others, and then some hacks here and there like most complex analytical systems. Some of it vendor shenanigans but some of it is specific features.

Not saying these shouldn't be used together, but even then, increased complexity will pay only in very limited scenarios. The generic SQLite can perhaps handle 80% of all wordpress needs.

Postgres made gigantic leaps in recent years - both in performance and feature-set. I don't think ever comparing the new contenders with daddy is fair. But then there are the DuckDB advocates who claim it pioneered spatial, which is so much not true.

Postgres is amazing system, which is also available free. We don;t have too many of these, and too many aging that well.

Not having a dependency on a running service can be an excellent reason to use tools like DuckDB.