> I'm fairly sure that whatever SQL Alchemy could do with a monstrously complex data-relationship views can do with better performance (the further the abstraction gets from the engine the less performance optimization it can do).

if you have the option to use materialized views, that can be helpful when appropriate, however materialized views have their own issues, not the least of which is that they need to be refreshed in order to have current data, they can take up a vast amount of storage, not to mention a lot of databases don't support them at all. It should not be necessary to emit CREATE MATERIALIZED VIEW with super-user privileges and to build the infrastructure to store them and keep them up-to-date for every query one needs to write or modify that happens to have some degree of composed complexity.

you don't need an ORM for these queries either, just a composable query builder (like SQLAlchemy Core) that allows the composition task to be more easily organizable in application code.

none of this means you can't use views but it's unnecessary to dictate that they should be the only tool available for dealing with large composed queries.

> I'm fairly sure that whatever SQL Alchemy could do with a monstrously complex data-relationship views can do with better performance (the further the abstraction gets from the engine the less performance optimization it can do).

SQL Alchemy will spit out SQL query. Whatever the DB engine can do with queries hand-written on top of views, it can also do it with the query generated by SQL Alchemy.

> Whatever the DB engine can do with queries hand-written on top of views, it can also do it with the query generated by SQL Alchemy.

No, on two levels. Firstly, there are many features in SQL that an ORM will not support (e.g. no substitute for a materialized view).

Secondly, once you get really good at SQL, you learn that very tiny seeming things can make the difference between a query running for an hour or a second (e.g. case-insensitive search against an indexed column). Part of being expert in DB technologies is knowing how/why some ways of writing a query are very fast, and others are very slow. The idea of an ORM is to hide that complexity, which is fine for a toy todo-mvc app. But once you start querying tables with 100k rows you need to understand that complexity and master it if you want to write a fast query.

> Secondly, once you get really good at SQL, you learn that very tiny seeming things can make the difference between a query running for an hour or a second (e.g. case-insensitive search against an indexed column).

SQLAlchemy supports case-insensitive searches, per-column / per-expression collation settings, index and other SQL hint formats for all databases that support them, e.g. SQLAlchemy's query language supports most optimizing SQL syntaxes, with the possible exception of very esoteric / outdated Oracle things like which table you list first in the FROM clause (use index hints instead). We are adding esoteric performance features all the time to support not just SQL-level tricks but driver level tricks too which are usually much more consequential, such as the typing information applied to bound parameters matching up for indexes as well as special driver-level APIs to improve the speed of bulk operations.

SQLAlchemy has been around for thirteen years, plenty of SQL experts have come along and requested these features and we implement them all. Feel free to come up with examples of SQL-expert level performance optimizations that SQLAlchemy doesn't support and we'll look into them.

Yeah, don't get me wrong, I haven't used SQL alchemy and I'm not trying to besmirch it. I'm not even sure we disagree.

What I'm trying to challenge is the philosophy that an ORM is an adequate facade in place of learning how databases work. My point about views is that in my experience, the answer to disgusting queries is cleaning up the DB design (and views can be the tool to accomplish this). My point about case-insensitive searching (you can create a case-insensitive index if you want) is that a lot of db-performance stuff just can't be solved on the query side alone anyways.

It sounds like SqlAlchemy is designed with a lot of flexibility around how queries are run, so maybe you agree that understanding what's going on beneath the hood is important to handle these complicated cases.

> What I'm trying to challenge is the philosophy that an ORM is an adequate facade in place of learning how databases work.

Thank you for this response and I agree, we are likely on the same page. I don't know that anyone actually espouses that philosophy. This is the anxiety that ORM skeptics have, and certainly you get beginners who rush into using ORMs not knowing what they are doing, but if someone wants to be a DB expert, I'm pretty sure they go to read about databases :) These ORM beginners will fail either with the ORM or without out. I guess the idea is you'd prefer they "fail fast", e.g. the ORM covers for them while they proceed to screw up more deeply? This is arguable; if you've seen much of the non-ORM raw DB code I've seen, it too fails pretty hard. But even with this argument, if ORMs produce the problem of incompetents who are not found out fast enough, why hoist the denial of useful tools to those developers who do know what they're doing.

You have shifted the discussion from ability of DB engine to optimize queries to the ability of a developer to write fast queries.

But in any case, we are not discussing some abstract ORM whose "idea is to hide complexity", but SQL Alchemy whose idea (one of them, at least) is to allow you to write composable queries yet still retain full power of SQL.

You are correct about needing to understand the underlying dB to be able to optimise it. I consider myself lucky to have come from a raw sql background and to have a deep understanding about how the query planners work.

You are incorrect in your other assertion. Sqlalchemy allows for optimising your queries at runtime in a way that just isn’t available to sql views. The beauty of sqlalchemy is that allows for arbitrary composition of blocks of sql. I too have had to fight with dbas in a previous life because they didn’t want me to construct a query in code (non sqla), but I eventually won because I was magnitudes faster because I had runtime knowledge they couldn’t use.