I've seen both extremes of this. On one end, you have applications that execute thousands of SQL queries for each page load, for populating a table with some d

I've seen both extremes of this. On one end, you have applications that execute thousands of SQL queries for each page load, for populating a table with some data or something like that, which has bunches of rules for what should be displayed, all implemented as nested method calls (e.g. the service pattern) in your application. It's a performance nightmare when you get more data, or more users. On the other end, you have an application where your back end acts just as a view for a DB that has all of the logic in it. There will rarely be proper tests for it. There will rarely be any sort of logging or observability solutions for this in place, the discoverability will be pretty bad, debugging will often be really bad, versioning of changes will also be pretty awkward, but at least the performance will typically be okay. Just look at the JetBrains Survey from 2021: https://www.jetbrains.com/lp/devecosystem-2021/databases/#Databases_do-you-debug-stored-procedures https://www.jetbrains.com/lp/devecosystem-2021/databases/#Da... Do you debug stored procedures? 47% Never 44% Rarely 9% Frequently Do you have tests in your database? 14% Yes 70% No 15% I don't know Do you keep your database scripts in a version control system? 54% Yes 37% No 9% I don't know Do you write comments for the database objects? 49% No 27% Yes, for many types of objects 24% Yes, only for tables If something that most would consider to be a "good practice" isn't done, then clearly that's a bit of a canary about the state of the technology and the ecosystem around it. Consider that databases are very important for most types of systems, and yet about half of people don't debug their stored procedures, most people don't have tests for them, only about half version their scripts and about half don't bother with comments. I'm pretty much convinced that it's possible to write bad software regardless of the approach that's used. In my mind, the happy path for succeeding in even sub-optimal circumstances is a bit like this: - make liberal use of DB views for querying data, if you have a table in your app, it should have a matching DB view, which will also make debugging easier - make use of in-database processing only when it makes a lot of sense and anything else would be a horrible choice (e.g. ETL or batch processes/pipelines), have log tables and such regardless - for most other concerns (e.g. typical CRUD), write app logic: most back end languages will have better support for observability and tracing, logging and debugging, as well as scaling for any expensive operations - still, be wary of the N+1 problem, that might mean that you don't have enough views, or that you're not using JOINs for your queries properly - also, look into using something like Redis for caching, S3 (or something compatible, like MinIO) for binary blobs and something like RabbitMQ for task queues, just because you can shove everything into the DB doesn't mean that you should, sometimes these specialized solutions will have better support and more standardized libraries, than whatever you can concoct