I'm studying up on clean and as a result am quite dramatically rethinking a great deal of how I design and write software.

I've thing I'm still wrestling with however, is for business rules like "on save updates to some item, first load All the list of items I have permission to view/edit etc, confirm that this item is in the list, and that the item category is not currently locked from use, (and other rules etc etc)".. because that is a (complex but not atypical) business rule, and so should be handled in the application domain rather than push business logic into the db/persistence layer.

However it seems to me that to efficiently check​ these conditions it is often going to be best handled with a nicely crafted db query, rather than loading all data into the application domain...

Without prematurely optimization, what's a recommended approach or some uncle Bob articles dealing with this question? Or would he say "validate in the domain until it becomes a problem"??

I am really struggling to find any good examples / samples for anything other than the most basic of use cases.


Hi all, thanks for the replies. I should have been clearer, I've been writing (mostly web app) software for a long time, and have definitely already experienced and agree with all the topics you collectively describe (validate by backend, don't trust client data, generally speaking chase raw efficiency only when required, however acknowledge strengths of the db tools when available, etc etc) and have gone through the developer learning lifecycle of "throw it all together" to "build a giant fat controller with N-tiers applications" code trends, and now really liking and investigating the clean / single responsibility style etc, basically as the result of a few projects recently that evolved into quite clunky and widely-distributed business rules as the projects evolved and further client requirements came to light.

In particular, I'm looking at Clean style architecture in the context of building REST apis for client-facing as well as internal-usage functionality, where many of the business rules might be much more complex than basically every example you see on the net (even by the Clean / Hex architecture guys themselves).

So I guess I was really asking (and failed to state clearly) about how Clean and a REST api would sit together, where most MVC stuff you see these days has incoming request validators (e.g FluentValidation library in .NET), but where many of my "validation" rules are not so much "is this a string of less than 50 characters" but more "can this user calling this usercase/interactor perform this operation on this collection of data given that some related object is currently locked by Team X until later in the month etc etc"... those kind of deeply involved validations where LOTS of business domain objects and domain rules are applicable.

Should I spin those rules out into a specific kind of Validator-object type to accompany each usecase-interactor (inspired by the FluentValidator project but with more business logic and data access involved), should I treat the validation somewhat like a Gateway, should i put those validations IN a gateway (which i think is wrong), etc etc.

For reference, I am going off several articles like this, but Mattia doesn't discuss validation much.

But I guess the short answer to my question is much like the answer that I have accepted: "It's never easy, and it depends".

  • 3
    There's often a difference between being "correct" and being "practical." Given the choice, which do you prefer? Commented Jun 22, 2017 at 15:23
  • "load All the list of items" does not look like a business rule, it seems to be diving too much into implementation details. If you can satisfy the rule by using a db query, without loading anything, why does the rule say "load"? Commented Jun 22, 2017 at 17:20

4 Answers 4


Validation of data entry is one of those things where everyone starts out trying to make it pure and clean and (if they're smart about it) eventually gives up, because there are so many competing concerns.

  • The UI layer must do some forms of validation right there on the client page/form in order to provide realtime feedback to the user. Otherwise the user spends a lot of time waiting for feedback while a transaction posts across the network.

  • Because the client often runs on an untrusted machine (e.g. in nearly all web applications), these validation routines must be executed again server side where the code is trusted.

  • Some forms of validation are implicit due to input constraints; for example, a textbox may allow only numeric entry. This means that you might not have a "is it numeric?" validator on the page, but you will still need one on the back end, somewhere, since UI constraints could be bypassed (e.g. by disabling Javascript).

  • The UI layer must do some forms of validation at the service perimeter (e.g. server-side code in a web application) in order to insulate the system against injection attacks or other malicious forms of data entry. Sometimes this validation isn't even in your code base, e.g. ASP.NET request validation.

  • The UI layer must do some forms of validation just to convert user-entered data into a format that the business layer can understand; for example, it must turn the string "6/26/2017" into a DateTime object in the appropriate time zone.

  • The business layer should do most forms of validation because, hey, they belong in the business layer, in theory.

  • Some forms of validation are more efficient at the database layer, especially when referential integrity checks are needed (e.g. to ensure that a state code is in the list of 50 valid states).

  • Some forms of validation must occur in the context of a database transaction due to concurrency concerns, e.g. reserving a unique user name has to be atomic so some other user doesn't grab it while you are processing.

  • Some forms of validation can only be performed by third party services, e.g. when validating that a postal code and a city name go together.

  • Throughout the system, null checks and data conversion checks may occur at multiple layers, to ensure reasonable failure modes in the presence of code flaws.

I have seen some developers try to codify all the validation rules in the business layer, and then have the other layers call it to extract the business rules and reconstruct the validation at a different layer. In theory this would be great because you end up with a single source of truth. But I have never, ever seen this approach do anything other than needlessly complicate the solution, and it often ends very badly.

So if you're killing yourself trying to figure out where your validation code goes, be advised-- in a practical solution to even a moderately complex problem, validation code will end up going in several places.

  • If you consider that you're UI manage all user's feedback, you can just push most of the validation check in database and only keep what you can't do in it at the business layer. Problem arise if you design a full backend API with a very detailled message troubleshooting.
    – Walfrat
    Commented Jun 27, 2017 at 7:36
  • Doing the validation in the domain layer doesn't mean that you have to do any network operations. it also checks the offline validation and return errors if any or process to network process then. Commented Jan 27, 2022 at 12:49

Validation is part of the business layer.

The point is: business logic in DAOs will invalidate the concept of DAOs. To do validation in any higher layer will result in redundant validation if you call business operations from another usecase.

Maybe you evaluate some security in the UI. But that is optional as the secured domain objects will do the important job. In the UI will make Components visible or invisible depending on the permissions the current logged in user has. But this is only part of the user experience. You do not want the user let run into security exceptions everytime he tries to perfom an action he is not allowed to.


You might want to check your perspective about who’s doing what vis-à-vis validation. Is it the DB, where you know you’re working with the DB? Or is it a service (that happens to be backed and controlled by DB operations). On my project every aggregate root has a list of groups that can read it and a list of modifiers. When the code looks for a specific root or a list of roots the user can see, all of the details are hidden behind a service that takes the user id and the extra parts of look up context like where the tile starts with “blah”. The code doesn’t care that the DB performs an exists check to see if the user’s groups exist in the readers’ groups. It merely expects a list with or without content based upon what ever the service, which is defined by contract only, provides.

This applies all down the layers. Uniformity of validation is the key. Put as much of your validation in domain as possible. Return constraints with your api. I’m the end don’t think of constraints coming from X library or Z storage, but from the service.


If some validation logic is expressed the simplest and most clearly in the form of a database query, then go ahead, you have your answer. But efficiency should only be a concern if you have a known performance problem, otherwise it is premature optimization.

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