Tutorial :Should the data access layer contain business logic?


I've seen a trend to move business logic out of the data access layer (stored procedures, LINQ, etc.) and into a business logic component layer (like C# objects).

Is this considered the "right" way to do things these days? If so, does this mean that some database developer positions may be eliminated in favor of more middle-tier coding positions? (i.e. more c# code rather than more long stored procedures.)


Data access logic belongs in the data access layer, business logic belongs in the business layer. I don't see how mixing the two could ever be considered a good idea from a design standpoint.


If the applications is small with a short lifetime, then it's not worth putting time into abstracting the concerns in layers. In larger, long lived applications your logic/business rules should not be coupled to the data access. It creates a maintenance nightmare as the application grows.

Moving concerns to a common layer or also known as Separation of concerns, has been around for a while:


The term separation of concerns was probably coined by Edsger W. Dijkstra in his 1974 paper "On the role of scientific thought"1.

For Application Architecture a great book to start with is Domain Driven Design. Eric Evans breaks down the different layers of the application in detail. He also discusses the database impedance and what he calls a "Bounded Context"

Bounded Context

A blog is a system that displays posts from newest to oldest so that people can comment on. Some would view this as one system, or one "Bounded Context." If you subscribe to DDD, one would say there are two systems or two "Bounded Contexts" in a blog: A commenting system and a publication system. DDD argues that each system is independent (of course there will be interaction between the two) and should be modeled as such. DDD gives concrete guidance on how to separate the concerns into the appropriate layers.

Other resources that might interest you:

Until I had a chance to experience The Big Ball of Mud or Spaghetti Code I had a hard time understanding why Application Architecture was so important...

The right way to do things will always to be dependent on the size, availability requirements and lifespan of your application. To use stored procs or not to use stored procs... Tools such as nHibrnate and Linq to SQL are great for small to mid-size projects. To make myself clear, I've never used nHibranate or Linq To Sql on a large application, but my gut feeling is an application will reach a size where optimizations will need to be done on the database server via views, Stored Procedures.. etc to keep the application performant. To do this work Developers with both Development and Database skills will be needed.


Separation of layers does not automatically mean not using stored procedures for business logic. This separation is equally possible:

Presentation Layer: .Net, PHP, whatever

Business Layer: Stored Procedures

Data Layer: Stored Procedures or DML

This works very well with Oracle, for example, where the business layer may be implemented in packages in a different schema from the data layer (to enforce proper separation of concerns).

What matters is the separation of concerns, not the language/technology used at each level.

(I expect to get roundly flamed for this heresy!)


It really depends on the requirements. Either way as long as it's NOT "behind the button" as it were. I think stored procedure are better for "classic" client server apps with changing needs. A strict middle "business logic" layer is better for apps that need to be very scalable, run on multiple database platforms, etc.


If you are building a layered architecture, and the architecture contains a dedicated business layer, then of course you should put business logic there. However, you can ask any five designers/architects/developers what 'business logic' actually is, and get six different answers. (Hey, I'm an architect myself, so I know all about 'on the one hand, but on the other'!). Is navigating an object graph part of the data layer or business layer? Depends on which EAA patterns you are using, and on exactly how complicated/clever your domain objects are. Or is it perhaps even part of your presentation?

But in more concrete terms: database development tools tend to lag behind Eclipse/Visual Studio/Netbeans/; and stored procedures have never been extremely comfortable for large-scale development. Yes, of course you can code everything in TSQL, PL/SQL &c, but there's a price to pay. What's more, the price of having several languages and platforms involved in one solution increases maintenance costs and delays. On the other hand, moving data access out of reach of DBA's can cause other headaches, especially with shared infrastructure environments with any kind of availability requirements. But overall, yes, modern tools and languages are currently moving logic from the data(base) layer into the application layer. We'll have to see how well it works out and scales.


The reason I've seen this trend is that LINQ and LINQ to SQL ORM give you a nice type-safe alternative to stored procedures.

What's "right" is whether you benefit from doing this personally.


Yes, business logic should be in the business logic layer. For me this is the biggest drawback of using store procedures for everything and thus moving some of the business rules to the db, I prefer to have that logic in the BLL in have the DLL only do communication with the db


It is ALWAYS a good idea to separate your layers. I can't tell you the number of times I've seen stored procedures that are VERY gnarly from lots of business logic written into the sproc. Also if you modify your complex stored procedure for whatever reason, you have the potential to break EVERYTHING that uses it.

Us devs at my company are moving to LINQ w/ the EF and dismissing the stored procedure unless we absolutely need it. LINQ and the EF make separating our layers a lot easier...when the EF is not being difficult. But that's another rant. :)


There will likely always be some level of business logic in the data layer. The data itself is a representation of some of that logic. For instance, primary keys are often created based on business logic rules.

For example, if your system won't allow an order to have more than one customer is part of the business logic, but it's also present (or should be) in the Data layer.

Further, some kinds of business rules are best done on the database itself for efficiency reasons. These are usually stored procedures, and thus exist in the data layer. An example might be a trigger that goes off if a customer has spent more than $X in a year, or if a ship-to is different from a bill-to.

Many of these rules might be handled in the business layer as well, but they also need a data layer component. It depends on where your error handling is.


Business logic in the data layer was common in client/server apps, as there really was no business logic layer per se (unless you could really, seriously prevent anyone from connecting to the database outside the application). Now that web apps are more common, you're seeing more 3- and 4-tier apps (client+web server+app server+database server), and more companies are following best practices and consolidating business logic in its own tier. I don't think there will be any less work for database developers, they'll probably just become the ones that write the business logic layer (and let an ORM tool write most of the database layer).


There are also technical reasons/limitations to be considered when planning where to author the business rules.

In most LOB applications centralization and performance pushes developers to use the database it self as the primary Business Layer, so in a sense, DAL and BL is mixed or unified.

A typical example would be the field that calculates the current location of a rental item, a piece of information that should be available for one or for many listed items, making an SQL view with a User Defined Function the most powerful candidate to hold the rule.

The above example is valid of course if a specific database design and processes implementation is preferred, but I just want to point out that in real world, we choose based on technical limitations and other principles, more often than we do for organizing our code.


The perfect world doesn't exist. It's about elegance versus what works better. Executing complex SQL queries inside data access layers is much more performative than making a service to ask data many times and then merging and transforming them. When you make complex queries you are putting business logic in those queries.

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