While I understand your point, there’s a mistake that I see far too often in the industry. Using Relational DBs where the data model is better suited to other sorts of DBs. For example, JSON documents are better stored in document DBs like mongo. I realize that your use case doesn’t involve querying json - in which it can be simply stored as text. Similar mistakes are made for time series data, key-value data and directory type data.
I’m not particularly angry at such (ab)uses of RDB. But you’ll probably get better results with NoSQL DBs. Even in cases that involve multiple data models, you could combine multiple DB software to achieve the best results. Or even better, there are adaptors for RDBMS that make it behave like different types at the same time. For example, ferretdb makes it behave like mongodb, postgis for geographic db, etc.
While I understand your point, there’s a mistake that I see far too often in the industry. Using Relational DBs where the data model is better suited to other sorts of DBs. For example, JSON documents are better stored in document DBs like mongo. I realize that your use case doesn’t involve querying json - in which it can be simply stored as text. Similar mistakes are made for time series data, key-value data and directory type data.
I’m not particularly angry at such (ab)uses of RDB. But you’ll probably get better results with NoSQL DBs. Even in cases that involve multiple data models, you could combine multiple DB software to achieve the best results. Or even better, there are adaptors for RDBMS that make it behave like different types at the same time. For example, ferretdb makes it behave like mongodb, postgis for geographic db, etc.