You can (and should) use them for simple queries. You have a list of entities you want to query and filter, that's going to be fine. Joins are fine. But if you're doing some complex analysis, an ORM is the wrong tool. That doesn't mean it's a poor abstraction, or difficult to follow, or something to be avoided. It's not the right tool for that job. For the job it's designed for, it's going to save a lot of effort.
SQL is great for analysis -- it's pretty much what it's designed for. But for bringing data into your app and modifying it, SQL is cumbersome and verbose. If you're loading data into objects then you're just creating your own personal ORM anyway.
In ActiveRecord, there's a method called find_by_sql. You can't call it directly; it's a class method on an ActiveRecord model. So you have to choose which of your ActiveRecord models should be used to instantiate the rows of your result set. (What if your result set doesn't really match any of your models? Pick one arbitrarily.) Your SQL has some extra columns. What happens to the data in those columns? They get monkey-patched onto the individual objects. (Which is stupidly expensive in Ruby.) Other than that, the individual objects are fine. They even have all your smart instance methods, which may or may not behave properly with all the ad-hoc monkey patching.
If you tried to short-circuit all of that nonsense, you tend to get arrays of hash tables. Which is, in my opinion, already a perfectly adequate interface!
I don't want to sound like the ORM defender, but I'm not sure I understand.
This sounds like a deficiency of Ruby and the ActiveRecord record model. In Java, for example, you'd just write a new POJO for your query, which isn't exactly difficult. There are no "smart methods" or whatever.
It is a valid criticism that this can proliferate data classes, but that depends on the application.
results = ActiveRecord::Base.connection.execute(sql)
Yes, both of these things can be solved through disciplined modularisation of ORM logic, but in my personal experience across multiple companies, most developers simply aren’t that disciplined and treat ORM code as any other application code, instead of treating it as the remotely executed database code that it actually is.
In my experience, writing raw SQL (through https://www.hugsql.org/ in my case), you are instead encouraged to think of them as separate and carefully consider the boundaries, which helps keep the queries and application logic modular and allows for more carefully crafted queries that minimise roundtrips and data shuffling.
Again, this has been my experience, across a number of companies. Perhaps your experience differs, in which case, I’m jealous.
With any of the ORMs I've used, as soon as you do something even slightly unorthodox like using a view, you're on your own.
If you're on your own using a view of all the simple shit, you're using an awful and pointless ORM.
It's the perfect type-safe abstraction on top of raw SQL.
https://github.com/ServiceStack/ServiceStack.OrmLite
https://github.com/CollaboratingPlatypus/PetaPoco
Any errors you get are likely a result of the underlying database/provider (foreign key constraints, etc).
You should never write raw SQL (if possible). You don't need an ORM to achieve that.
And by "drop into", this typically means writing custom stitching code that stitches the SQL cursor results back into the models again. It's rarely straightforward.
The biggest selling point is a massive reduction in boilerplate code. Database agnostism is a feature that almost nobody ever uses, so who cares! Your proposed alternative is engine-specific SQL so you lose either way. At least with an ORM, you'd lose significantly less. You'd just have to deal with the places you used SQL. Which, in my experience, is pretty small and pretty specific.
> this typically means writing custom stitching code that stitches the SQL cursor results back into the models again.
I often feel like people who complain about ORMs have either actually never used one or used a poor one. As long as my query matches the structure of my object(s) I don't need any stitching code. And if they didn't match, I wouldn't write stitching code because that would be waste of time.
If I'm writing a custom query, I'm probably not looking to integrate into the model anyway -- if it's used for reporting I'd just take the results as is. If I'm writing a query specifically to get a matching model object (to manipulate) I'm going to get the whole model and no stitching would be required.
I haven't heard anyone talk seriously about database-agnosticism since the very early 2000s. Maybe some commercial products still try (choose MS or Oracle!), but it's rare nowadays.
The primary selling point of an ORM is that it abstracts marshaling/un-marshaling rows to/from entities. Instantiating and persisting entities to relational storage.
> And by "drop into", this typically means writing custom stitching code that stitches the SQL cursor results back into the models again. It's rarely straightforward.
That's not typical in most uses I've seen. Far more typical are things like:
- Go straight to SQL for reporting, since that's what SQL does. Useful in reporting contexts, and also for list/filter UI screens.
- Use raw SQL to query a list of entity IDs for updating based on some complex criteria. Iterate over the identifiers and perform whatever logic you need to before letting the ORM handle all the persistence concerns.
Do you use the same database engine for your unit and integration testing as you do production? I don't. I use sqlite for unit and local integration testing, and aurora-mysql for production.
As a side note, I quite literally can't use aurora-mysql for local unit and integration testing. It doesn't exist outside AWS.
That's a recipe for tests that don't catch edge cases.
An integration test that doesn't use the same DB as production is unsatisfactory.
Integration tests should run against a test environment, otherwise, what integration are you testing? I don't see the value in writing integration tests that test the integration between my code and a one-off integration test DB that exists solely for the purpose of integration testing.
Also if you’re using only the subset of MySQL that is supported by SQLite, you’re missing out on some real optimizations for bulk data loads like “insert into ignore...” and “insert...on duplicate key update...”. Besides that, the behavior of certain queries/data types/constraints are inconsistent between MySQL and every other database in existence.
Finally, you can’t really do performance testing across databases.
You can use mysql though...
Yeah, don't do that.
Queries look like:
SELECT u FROM ForumUser u WHERE (u.username = :name OR u.username = :name2) AND u.id = :id
Where ForumUser is your model.
https://www.doctrine-project.org/projects/doctrine-orm/en/2....
[0] https://github.com/martin-georgiev/postgresql-for-doctrine [1] https://www.doctrine-project.org/projects/doctrine-dbal/en/2...
1. If the suggested alternative is writing only SQL from the get-go, then why would one even care about database agnosticism?
2. A large part of SQL is compatible between databases, so this might be a non-issue.
3. You can always use specific in-database abstractions such as Views and Stored Procedures for those complicated bits.
B. if it were, that only argues that you don't use the ORM in the latter case.
You can have an ORM in your project and still fall back to plain old SQL if you like. It's not an "either-or" thing.
I wouldn't mind writing queries in SQL so I don't have to learn a new ORM for every language I use. However I like that ORMs unmarshal results for me in objects / tuples / maps of the language sparing me the work.
For complicated things I write SQL and possibly decode the results manually.
If you know a problem is going to be complicated, you know to use SQL.
If you don't know if a problem is going to be complicated, you can default to SQL and decide to use the ORM later if it's a good fit once you've got more problem details.
This is not a very compelling argument to use ORMs. It is saying "it makes easy things easier". This doesn't really buy you much value. The simple things are already simple. Bringing in a very large, complicated external dependency to make simple things simpler, is not a good idea.
>If you're loading data into objects then you're just creating your own personal ORM anyway.
By this definition, the Postgres driver I use for node is an ORM as it takes a row of string/type identification codes and turns them into javascript objects and javascript types. It isn't an ORM though, that is not what an ORM does. An ORM converts one paradigm into a completely different paradigm, which is why it fails and is a terrible idea.
Django, just as an example, does a magnificent job with its built-in ORM. Millions of developers use it, and they are not all fools. A fool is someone who would set out to build a simple-to-intermediate CRUD web app by writing SQL.
> A fool is someone who would set out to build a simple-to-intermediate CRUD web app by writing SQL.
\u{1f644}
SQL works great for simple-to-intermediate CRUD web apps too.
No it makes simple things easy. Simple things in raw SQL are bloody complicated. Even just getting data, manipulating it, and saving it is at least twice as difficult in maintainability and lines of code than using an ORM.
> An ORM converts one paradigm into a completely different paradigm, which is why it fails and is a terrible idea.
I'm not sure where people get the idea that ORMs fail at their job. They really don't. They do it very well and we're all quite happy.
All the anti-ORM arguments here about how ORMs fail at completely different jobs other than mapping objects to RDBMS operations. Well duh. Nobody complains about cars that can't fly and planes that can't fit on the highway but when ORM can't cook bacon it doesn't fit the paradigm.
That has not been my own experience outside of the most trivial queries. Once any amount of complexity is introduced, I find that ORM-based queries often make it difficult to really see whats going on with indexes and locking, I can’t just paste a query (eg to use EXPLAIN) without finding it in a query log first and, unfortunately, in my experience its rare to find teams disciplined enough to not treat ORM code as if it were normal application code (ie don’t mix it into your application logic), so often end up with a few database/application roundtrips, doing filtering in the wrong place etc. Yes that last one isn’t technically the fault of the ORM, but when I see it again and again in real world code, I start to think that most developers don’t have the discipline to be careful with ORM code while when not using ORM’s and writing raw SQL outside of your applications code, you have no choice. Not the ORM’s fault, but still a symptom of using one that I’ve experienced in multiple teams.
Things don't usually start out bad, but they become bad only after you have a more complex codebase with many users (ie many queries). Its at this point that you need to know what a query is doing, yet its at this point that the query logs are full of queries, so finding the ones I want becomes hard. Putting a trace on the queries also becomes hard when you have a large codebase where the query logic is intermingled with application logic. I mentioned this in my comment.
You say it's my "refusal to want to change the way you work that is the issue", but I never chose to work that way. All of the codebases where I've had this issue were inherited: I was not the one to decide to work like this and I did not mix the query logic into the application logic. But that was my point: I've had the same experience across multiple teams in multiple companies, so blaming the developers seems like a cop out and not much of a solution. I'll happily adapt the way I work, but I can't force existing teams to change. Maybe discipline could fix it, but I have not experienced this discipline anywhere I've worked. But sure, its my fault somehow.
Unless you’re programming in assembly, everything you do is being converted into another paradigm that is what every compiler and interpreter does.
How does an ORM prevent you from using any SQL features?
When you do the sorts of complicated things that are out of scope for an ORM, you do them in SQL. I don't see any incompatibility.
Back in the day when I was doing C, there were times when we just couldn’t get the speed we needed from the compiler. I wrote inline assembly. Does that mean C was unsuitable because it was incompatible with our performance requirements?
You can theoretically express any standard SQL query in LINQ even though outer joins can be obtuse at first. The translation may not be as optimal as hand written sql, but no compiler can translate code into assembly that would be as optimized as someone who could hand roll their own. We decided decades ago that high level languages were worth the trade off most of the time.
This is where I disagree. I dislike having a value which is the entity. The basic lesson from relational databases and later data oriented design is that you don't have an entity. All you have are aspects that are related.
All of these questions require deep knowledge of the inner workings of the ORM, when in SQL, this is a lot more straightforward.
The Django ORM takes take a whole of an hour to read, and after that you have 90% of the use cases covered. Considering that I've been using that framework for many years now, the overhead of that knowledge is irrelevant.
Simple tasks are done maybe thousands of times in any one application. It's the complex tasks are rare.
That's not a fair comparison unless you include the time and effort involved in creating your ORM models, before you can even write those 3 lines of ORM code. The effort to construct those models isn't even fully amortized over your project, since it must be maintained through schema migrations.
ORMs are like putting on an exoskeleton to go buy groceries because it will let you carry your bags more easily. In my opinion, the complexity and indirection they introduce for accomplishing simple tasks do not justify their existence in the vast majority of cases.
It's no more difficult than building tables by hand. There isn't any extra work that you wouldn't also have to do when not using an ORM.
cursor.execute("""
UPDATE employees
INNER JOIN merits ON employees.performance = merits.performance
SET salary = salary + salary * percentage;
""")
It's not much more effort to type "create table employees" with all the fixings as it is to type "class employees" with all the fixings.
Depends on the ORM. Just like "raw sql mode", not every ORM supports that. It's not an inherent feature of being an object-relational mapper, it's part of the bells and whistles of some ORM packages. And I'm going to guess you're coming from the Python/scripting universe, because generating models in other languages is definitely more complicated.
But let's pretend that all ORM software can generate model definitions from the database. Just do the update then. I want to validate your argument that a simple update in SQL is "a lot more code especially if wiring up foreign relationships." If you think an ORM is much less code, or simpler, I'd like to see how.
In my API, I have models from my ORM. These can then be used for database migrations, which allows changes in my database structure to be checked in to version control.
From there, these models are obviously used for queries within my app. Generally, you are correct that generating a simple query with the ORM is not meaningfully easier than writing the SQL myself, with the one exception being that the ORM sanitizes inputs to my queries without me having to think about it at all, which is nice.
From there though, I can use the models from my ORM to automatically validate incoming requests to the API endpoints, as well as automatically serialize the results of my queries when I want to send a response back to the client. If you're not building a REST API, obviously this might not be particularly useful, but for someone that is, it has saved me a lot of work.
Finally, generally I find code in my code is a bit easier to debug than strings.
employee = new Employee() { Name = "Bob" }
employee.Manager = new Employee() { Name = "Jill" }
context.Employees.Add(employee)
context.SaveChanges()
The ORM is performing operations on objects -- it's pretty much right there in the name -- it's going to be a poor choice for bulk updates because that's not what it's for. But again, nothing stops you from using the right tool for the right job -- whether that be an ORM or raw SQL.
$db->employees->update({
salary => $Q{salary} + $Q{salary} * $Q{merit}{percentage}
});
The Hibernate repo is 700 thousand lines of java code!
There's a tendency amongst some (especially "enterprise" programmers) to forget that dependencies are also just code. If they break, you are on the hook too. You own that complexity.
A good SQL access library can validate queries against the database itself at build time.
await client.query(`
update table set c1 = $1, c2 = $2
where id = $3 and userId = $4
`, [c1, c2, id, userId]);See digging.
Whenever I get to the point where I'd do something gnarly with a query, I just fall back to SQL statements with results that the ORM can parse; or just dump directly into data structures and go from there, even if the originating tables still have ORMs.
If your framework/library/language doesn't let you skip the ORM - or populate the object with the results of a custom query - well, I'd say that's a failing of that ORM, not of ORMs in general.
I remember the very first time I had to do anything interactive on a web page. We had a long list of items in a table, and as a stopgap for adding search functionality we were going to sort the table by multiple columns.
Stack Overflow was still a twinkle it Atwood's eye. So I go googling about for stable sort implementations in Javascript and I find plenty. Except they all have the same problem. They were all slow as molasses. I should have taken it as a huge warning that none of these implementations used demos showed sorting of more than 10 items.
I needed to sort 100 items. 300 at the outside. Ultimately I had to go to source material and implement it myself.
Clearly there is some notion in the software community that market for ideas is inexhaustible. That the 'oxygen' in the room is infinite, and therefore I can interject whatever half-assed concept I had into it without costing anybody anything.
Virtually all of us, when we tackle a problem, try to do better than what is already on offer. But what if the thing on offer is truly, horrible? If my only goal is 'better' instead of 'good', then my alternative will be really bad. And in a field full of bad, who wants to be the person who introduces the 6th standard? The 8th?
Keep your dumb ideas to yourself, or put them in question form and ask people why
After someone posted Norvig's Sudoku solver, I was troubled by his statement about how many algorithms he'd have to implement so he just did brute force. So I took a whack at it, got fairly far down the deductive path before things got hard. But I'm not going to show it to everybody. The internet has been working on strategies for 10 years, and they've done way more algorithms than the ones I knew about. The best I've managed is to maybe simplify a couple rules, but I think one could argue that it's the bad definition of 'simple'. It can't handle as many cases, but I can explain it to anyone. Is that enough to add to the noise? Probably not.
Since then I keep using ORMs (because mapping the things you pull from the db to actual objects is undoubtedly good) but I write my queries by hand.
I also dislike ORMs that, by default, when you try to access an object you forgot to pull from the db with the query you wrote, automatically generate another query to pull the data instead of erroring out.
The argument I've made before when going down the path of ORMs has been: do we forsee needing to use this model code on a different database engine? Outside of simple toy applications, or needing to support different engines with the same code, I agree that ORMs are more trouble than they're worth.