The question is what kind of "more" is needed. Out of disk space or hitting CPU/mem limits? Splitting off a 2nd service which handles isolated functionality could help, migrating to larger storage could help, migrating some data to cold/external storage could help, eliminating low value high storage cost features could help.
The only "more" which pushes a move to client-server DB is a CPU- or memory-limited, not easily sharded, persistent service. But to have such a problem is highly uncommon. Usually optimization will solve such problems easily. I've seen Python services which use 1GB RAM/process, each process can handle 1 concurrent request, and there's only 20GB of RAM per instance. The solution there is to use one of many sane async frameworks to handle more than 1 concurrent request/process. Some problems, such as latency of DB queries/N+1s and the query complexity which ensues, will not even arise in the first place if you were using SQLite.
The only "more" which pushes a move to client-server DB is a CPU- or memory-limited, not easily sharded, persistent service. But to have such a problem is highly uncommon. Usually optimization will solve such problems easily. I've seen Python services which use 1GB RAM/process, each process can handle 1 concurrent request, and there's only 20GB of RAM per instance. The solution there is to use one of many sane async frameworks to handle more than 1 concurrent request/process. Some problems, such as latency of DB queries/N+1s and the query complexity which ensues, will not even arise in the first place if you were using SQLite.