It has a Brand object, and on the main page of the Web site, all of the brands that the store sells are listed on the left side. To display this menu of brands, all the site needs is the integer BrandId and the string BrandName. But the Brand object contains a whole boatload of other properties, most notably a Description property that can contain a substantially large amount of text about the Brand. No two ways about it, loading all of that extra information about the brand just to spit out its name in an unordered list is 1 measurably and significantly slow, usually because of the large text fields and 2 pretty inefficient when it comes to memory usage, building up large strings and not even looking at them before throwing them away.
One option provided by many ORMs is to lazy load a property. So we could have a Brand object returned to us, but that time-consuming and memory-wasting Description field is not until we try to invoke its get accessor. At that point, the proxy object will intercept our call and suck down the description from the database just in time. This is sometimes good enough but has burned me enough times that I personally don't recommend it:.
So what I've ended up doing is that in scenarios that require performance or are prone to database deadlocks, I create a separate interface that the Web site or any other program can call to get access to specific chunks of data that have had their query plans carefully examined. I used to think that this was cheating, subverting the OO object model. But in a practical sense, as long as you do this shortcut for displaying data, I think it's all right.
This will probably be a stored procedure anyway, writing the ADO. NET takes two seconds. People use ORM's for greater development productivity, not for runtime performance optimization. It depends on the project whether it's more important to maximize development efficiency or runtime efficiency. In practice, one could use the ORM for greatest productivity, and then profile the application to identify bottlenecks once you're finished. We can't generalize that the wildcard is always good or always bad.
Personally, I always name the columns in a query explicitly; I never use the wildcard in production code though I use it when doing ad hoc queries. It could be that the ORM framework is generating SQL queries to make sure all the fields are available in case you need them.
Linq to Sql , or any implementation of IQueryable , uses a syntax which ultimately puts you in control of the selected data. The definition of a query is also the definition of its result set. To begin, it is quite common when using an ORM for the table and the object to have quite different "shapes", this is one reason why many ORM tools support quite complex mappings. A good example is when a table is partially denormalised, with columns containing redundant information often, this is done to improve query or reporting performance.
When this occurs, it is more efficient for the ORM to request just the columns it requires, than to have all the extra columns brought back and ignored. Problem is, when a typical developer observes that the columns returned seem to be in a consistent order, the assumption is made that the columns will always be in that order, and then you have code making unwarranted assumptions, just waiting to fail.
Worse, that failure may not be fatal, but may simply involve, say, using Year of Birth in place of Account Balance. By explicitly requesting the fields you require, you ensure that your system will break rather than process the wrong information. I am not sure why you would want a partially hydrated object. Given a class of Customer with properties of Name, Address, Id.
I would want them all to create a fully populated Customer object. And NHibernate anyway allows you to do projections into other objects.
So if you had say a simply customer list where you displayed the ID and Name, you can create an object of type CustomerListDisplay and project your HQL query into that object set and only obtain the columns you need from the database. Friends don't let friends premature optimize. Fully hydrate your object, lazy load it's associations.
And then profile your application looking for problems and optimize the problem areas. So, do you have different kinds of MyThing objects, one for each column combo? No, I have read-only digest objects which only contain important information for things like lookups and massive collections and convert these to fully hydrated objects on demand.
The case you describe is a great example of how ORM is not a panacea. Databases offer flexible, needs-based access to their data primarily through SQL. My mechanism for doing this will be easily understood by any other developer taking over the project. In order to get the same flexibility from ORM, a lot more work has to be done either by you or the ORM developers just to get you back to the place under the hood where you're either getting all or some of the columns from the database as needed see the excellent answers above to get a sense of some of the problems.
And just another evidence of why you don't need an ORM: medium. Show 7 more comments. Active Oldest Votes. Just to give you a general idea, they are catalogued as: Mismatches Object-oriented concepts Data type differences Structural and integrity differences Manipulative differences Transactional differences Solving impedance mismatch Minimization Alternative architectures Compensation Contention Philosophical differences I think if you take the time to read the article you'll understand that the fact that ORM is sometimes described as an anti-pattern is in fact inevitable.
Improve this answer. Community Bot 1. Buzzwords for geeks, but I like them too! Totally agree Add a comment. But it is very nice not having to manually populate pojos, etc. Nathan Long Nathan Long 3, 3 3 gold badges 22 22 silver badges 27 27 bronze badges.
Raynos: You mean Fowler might have been Raynos - Perhaps authority isn't the best argument, but the OP said "in my experience". This is essentially an appeal to personal authority, so I think it's reasonable to counter with an appeal to authority and consensus. Besides, the term "anti-pattern" is itself about opinions. I've given examples of what other people think. NathanLong I was just pointing out that popularity and correct-ness are orthogonal. ActiveRecord is a different pattern, though certainly related.
Show 3 more comments. Jeremy Jeremy 4, 21 21 silver badges 21 21 bronze badges. Pros: It gets rid of "Magic Strings", or at least offers a once-and-only-once place to put them It allows me to work in an OO paradigm the entire time The code is easier to read The code built on top is easier to change It allows you to swap out your actual relational database without maintaning 2 separate repositories rarely done, but that's one big benefit if you need it. Cons: The code is harder to write , because It is not a sufficient abstraction -- you still have to be intimately familiar with what it's doing in the background I will say that it doesn't live up to the promise that most people initially hope for.
Scott Whitlock Scott Whitlock JasonTrue JasonTrue 8, 1 1 gold badge 31 31 silver badges 48 48 bronze badges. I am not sure what you mean by that. Your comment doesn't make much sense to me. In that an ORM makes a great way to access a DB with a ton of hard work done for you, but if you use it as a design pattern to pretend a DB is a collection of objects, it starts to fall over.
Which is what I thought you were saying. I don't think I've ever advocating using an ORM to pretend that you've got a magical object store that doesn't require you to understand how the database work.
I said precisely the opposite: If you understand object-oriented programming well AND how databases work, an ORM can help you produce more maintainable code. Tangurena Tangurena This answer is an answer. Like all answers, when written appropriately, can be quite useful. Using the low-level Database Driver modules is rather enticing. There is no overhead when generating a query for the database as we are manually writing the query. The overall dependencies our project relies upon is also minimized.
However, generating dynamic queries can be very tedious, and in my opinion is the biggest drawback of using a simple Database Driver. Consider, for example, a web interface where a user can select criteria when they want to retrieve items. If there is only a single option that a user can input, such as color, our query might look like the following:.
This single query works nicely with the simple Database Driver. We now need to support a few different permutations of this query:. The Query Builder ends up being a pretty nice tool in these situations. This relationship is similar to how something like TypeScript translates to JavaScript.
Using a Query Build is a fine solution as long as you fully understand the underlying SQL it is generating. Never use it as a tool to hide from what is happening at a lower layer. If you ever find yourself questioning what a generated query actually looks like you can add a debug field to the Knex instantiation call.
Doing so looks like this:. In fact, most of the libraries mentioned in this post include some sort of method for debugging the calls being executed. Thank you for reading and be sure to take this into consideration when you build your next project.
LogRocket is like a DVR for web and mobile apps, recording literally everything that happens while a user interacts with your app. Instead of guessing why problems happen, you can aggregate and report on problematic network requests to quickly understand the root cause. And when it comes to Node.
Therefore, i find this article good in this case. Smart developers are more concerned with how they can be efficient as developers how efficiently they can write the code , and ORMs are certainly a better solution for being efficient as a code writer.
Making your code efficient is not nearly as important as being efficient while making your code in most cases. This is such a shallow, one sided article, and it triggers me. I think this is your own bias. Some people are fluent in SQL before they ever touch an ORM and those people will be acutely aware of the points made in this article.
In the inverse, someone who is comfortable doing ordinary things with an ORM is immediately thrown in the deep end of the underlying query language when they have to do something a little out of the ordinary. Furthermore, you misunderstand the implications of point number two. This article is extremely important, and possibly much more than anyone can realize. Going by good software-engineering practices, abstraction can never be a positive approach, be it in imperative or declarative paradigms.
Hi, There is little research on which technique is faster. Will you write some content on it for my understanding. I have learnt so many things from your website. Yes, it is correct! As a result, I believe this post is appropriate in this situation. First of all, I have to point out that writing your own ORM is almost always a bad idea. There are lots of solutions on the market already. Your implementation is most likely going to become a clone of one of them, except that it will have fewer features and more bugs.
Because object-relational mapping is hard. There are fundamental differences in the OO-based and relational-based approaches. No ORM is able to marry them entirely well, neither will yours. Martin Fowler has a great article on this topic, check it our for more details. That presumably leaves us with the two options: either accept the shortcomings stated above or avoid using ORMs, falling down to SQL and abandoning the object-oriented paradigm.
The one that combines the benefits of the two approaches pretty nicely. ORMs are often taken as a replacement for the necessity to learn SQL, as well as various pitfalls you may run into with relational databases. The key point here is to define the area of application for ORMs so that we can employ their strengths and avoid their weaknesses.
So, what is it? Every application can be mentally separated into two parts: write model and read model. The former would be your write model and the latter - the read model. So, the trick is that ORMs are for the write models only.
They are good at mutating data, persisting your domain model, executing OLTP operations. Most of the problems attributed to ORMs vanish after we start following this guideline.
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