I actually make this calculation for most projects that I work on -- what level of traffic do I expect this to see? If it's a back-office function or is limited to a few hundred clients at a time, I don't even worry about performance.

But that said... writing native SQL queries wastes a month? Um, no. ORMs are convenient, but writing select, insert, update, and delete queries by hand isn't that hard. It's mildly verbose and you end up repeating yourself lots so it's annoying, particularly if you (like me) have the kind of programmer's mind that constantly wants to factor that out. But it's doable without adding a high factor to development time.

Writing anything is fast. It's maintaining it that becomes a problem.

I build a web app for that is only used by maybe 3 persons.

Still, inefficiency is a huge issue. I need to be close to desktop-like performance for data entry, and that requiere both insert/read performance (that are executed in the same block and compromise several queries) below 1 seconds.

Request/seconds is not the metric that matter.

Is the seconds/for user(s) main activity.

Depends on the application. In e-commerce and I believe many other industries as well will depend on fast responses for conversions. For example, a page that loads ~2 seconds will start to lose bounce rates/ conversions.

Of course full page cache is the first stopgap for this problem but you'll always have dynamic content.

> But wasting a month tryig to write native Sql queries can hurt your project a lot more.

Unless it would be the first contact a developer has with SQL, I really don't see how difference in time taken to query the database with an ORM vs SQL would be anything more than a couple of minutes, maybe an hour if you really have a hard time with it or your data model is really convoluted.

This really depends entirely on what your application is doing and how it generates and processes queries. Some things are just annoying to solve without an ORM / "query builder" / SQL-AST (unless you write a small ORM yourself).

i always take the approach of get it functionally complete first then optimize for performance. It's easier to track optimization bugs (which can be nasty) and you always have something to revert to that at least works.

I agree that 99% of all projects never push beyond what relational databases are capable of. I've seen developers who were tasked with writing basically a todo list say that they're going with a nosql database because RDBMs don't scale.

Even if you get 1 hit / day and that takes a long time to return, the ORM has failed your one customer. Inefficiency exists even at small scales with ORMs. If your developers don't know how to write SQL, let them learn. Or fire them if they won't.

> Inefficiency exists even at small scales with ORMs

ORMs are not inherently inefficient. And in my time I have seen plenty of n+1 style queries written with raw SQL.

Lazy loading often fetches too little and eager loading too much. Most orms select all columns in all tables regardless of need. The query translation and hydration overhead of transforming the data into objects even in a fast language are always going to be problems, it's just a matter of how big, over a system without the orm. Since orms are superfluous, every line of code in them adds unnecessary overhead. They are indeed inherently inefficient by definition.

> The query translation and hydration overhead of transforming the data into objects even in a fast language are always going to be problems

No they are not. Have you measured this in a real-world application? This overhead is negligible compared to the cost of the query itself. And without an ORM you still have to load the data into some kind of objects or data structures before you pass it to presentation, you will just have to write the code yourself.

But yeah, lazy loading in a loop will kill performance. So don't do that.

It's definetly not always going to be a problem, but sometimes it does. ORM is always slower than writing custom code, but it might be more than fast enough.

Surely it depends on the custom code in question if it is faster or slower than the similar ORM logic?

You may be able to write faster code, but unless you are Donald Knuth, you can't guarantee that any custom code you write will always be faster than some library.