I know the spanner marketing blurb says you can scale down etc. But I think in practice spanner is primarily aimed at use cases where you'd struggle to fit everything in a single postgres instance.
Having said that I guess I broadly agree with your comment. It seems like a lot of people like to plan for massive scale while they have a handful of actual users.
I said this in another comment, but I have seen _two_ applications in my career that actually had a request load that might warrant something like one of these databases. One was an application with double digit million MAU and thousands of RPS on a very shardable data set, which fit Spanner's ideal access pattern and performance profile pretty well, but we paid an absolute arm and a leg for the privilege and ended up implementing a distributed cache in front of Spanner to reduce costs. The other just kept the data set in memory and flushed to disk/S3 backup periodically because in that case liveness was more important than completeness.
In the first case, the database created as many problems as it solved (which is true of any large application running at scale; your data store will _always_ be suboptimal). A fancy, expensive NoSQL database won't save you from solving hard engineering problems. At smaller scales (on the order of tens-hundreds of RPS), it's hard to go wrong with any established SQL (or open source NoSQL if that floats your boat) database, and IMO Postgres is the most stable and best bang for your engineering buck feature wise.
Postgres/mysql shouldn't have much trouble doing thousands of RPS on a laptop for basic CRUD queries (i.e. as long as you don't need to do table scans or large index range scans). It's possible to squeeze a lot more than that out of them.
My team bought the "scale down" thing and got bit.
Using Spanner is giving up a lot for the scalability, and if you ever reach the scale where a single node DB doesn't make sense anymore, I don't know if Spanner is still the answer, let alone Spanner with your old design still intact. For one, Postgres has scaling options like Citus. Or maybe you don't need a scalable DB even at scale, cause you shard at a higher layer instead.
Having said that I guess I broadly agree with your comment. It seems like a lot of people like to plan for massive scale while they have a handful of actual users.