What do you suggest for Data Access layer? Using ORMs like Entity Framework and Hibernate OR Code Generators like Subsonic, .netTiers, T4, etc.?
For me, this is a no-brainer, you generate the code.
I'm going to go slightly off topic here because there's a bigger underlying fallacy at play. The fallacy is that these ORM frameworks solve the object/relational impedence mismatch. This claim is a barefaced lie.
I find the best way to resolve the object/relational impedance mismatch is to either use OOP exclusively and use an object database or use the idioms of the relational database exclusively and ignore OOP.
The abstraction "everything is a table" is to me, much more powerful than the abstraction "everything is a class." It takes less code, less intellectual effort and leads to faster code when you code to the database rather than to an object model.
To me this seems obvious. If your application is data driven then surely your code should be data driven too? Yet to say this is hugely controversial.
The central problem here is that OOP becomes a really leaky abstraction when used in conjunction with a database. Code that look perfectly sensible when written to the idioms of OOP looks completely insane when you see the traffic that code generates at the database. When that messiness becomes a performance problem, OOP is the first casualty.
There is really no way to resolve this. Databases work with sets of data. OOP focus on instances of classes. Trying to marry the two is always going to end in divorce.
So to answer your question, I believe you should generate your classes and try and make them map the underlying database structure as closely as possible.
Perhaps controversially, I've always felt that using code generators for the ADO.NET plumbing is fundamentally solving the wrong problem.
At some point, hopefully not too long after learning about Connection Strings, SqlCommands, DataAdapters, and all that, we notice that:
Such code is ugly
It is very boring to write
It's very easy to miss something if you're doing it by hand
It has to be repeated every time you want to access the database
So, the problem to solve is "how to do the same thing lots of times fast"?
I say no.
Using code generators to make this process quick still means that you have a ton of code, all the same, all over your business classes (or your data access layer, if you separate that from your business logic).
And then, if you want to do something generically (like track stored procedure usage, for instance), you end up having to customise your code generator if it doesn't already have the feature you want. And even if it does, you still have to regenerate everything all the time.
I like to do things once, not many times, no matter how fast I can do them.
So I rolled my own Data Access class that knows how to add parameters, set up and close connections, manage transactions, and other cool stuff. It only had to be written once, and calling its methods from a Business object that needs some database stuff done consists of one line of code.
When I needed to make the application support multithreaded database accesses, it required a change to the Data Access class only, and all the business classes just do what they already did.
There is no right answer it all depends on your project. As Simon points out if your application is all data driven, then it might make sense depending on the size and complexity of the domain to use non oop paradigm. I had a lot of success building a system using a Transaction Script pattern, which passed XML Messages around the system.
However this system started to break down after five or six years as the application grew in size and complexity (5 or 6 webs, several web services, tons of COM+ components, legacy and .net code, 8+ databases with 800+ tables 4,000+ procedures). No one knew what anything was, and duplication was running rampant.
There are other ways to alleviate the maintance then OOP; however, if you have a very complex domain then hainvg a rich domain model is ideal IMHO, as it allows for the business rules to be expressed in nice encapsulated components.
To answer your question, avoid code generators if you can. Code generators are a recipe for disaster, but if you do go with code generation do not modify the generated code. Also be sure to have a good process in place that is easy for developers to get the new generated code.
I recommend using either the following: ORM or hand roll a lightweight DAL. I am currently transitioning a project over to nHibernate off my hand rolled DAL and am having a lot of success; however, I like having the option of using either option. Further if you properly seperate your concerns (Data Access from Business Layer from Presentation) you can have a single service layer that might talk to a Dao (Data Access Object) that for one object is an ORM but for another is hand rolled). I like this flexibility as it allows to apply the best tool to the job.
I like nHibernate over a hand rolled DAL because while my DAL does abstract away most of the ADO.Net code you still have to write the code that takes a data reader to an object or an object and creates the parameters.
I've always preferred to go the code generator route, especially in C# where you can make use of extended classes to add functionality to the basic data objects.
Hate to say this, but it depends. If you find an ORM tool that fits your needs go for it. We wrote our own system in small steps while developing the application. We are using C++ and there are not that many tools out there anyway. Ours ended up being a XML description of the database, from that the SQL generation script and the basic object layer and metadata were generated.
Do your homework and evaluate theses tools and you will find a good fit for your needs.
Everyone I work with is obsessed with the data-centric approach to enterprise development and hates the idea of using custom collections/objects. What is the best way to convince them otherwise?
Do it by example and tread lightly. Anything stronger will just alienate you from the rest of the team.
Remember to consider the possibility that they're onto something you've missed. Being part of a team means taking turns learning & teaching.
No single person has all the answers.
If you are working on legacy code (e.g., apps ported from .NET 1.x to 2.0 or 3.5) then it would be a bad idea to depart from datasets. Why change something that already works?
If you are, however, creating a new apps, there a few things that you can cite:
Appeal to experiencing pain in maintaining apps that stick with DataSets
Cite performance benefits for your new approach
Bait them with a good middle-ground. Move to .NET 3.5, and promote LINQ to SQL, for instance: while still sticking to data-driven architecture, is a huge, huge departure to string-indexed data sets, and enforces... voila! Custom collections -- in a manner that is hidden from them.
What is important is that whatever approach you use you remain consistent, and you are completely honest with the pros and cons of your approaches.
If all else fails (e.g., you have a development team that utterly refuses to budge from old practices and is skeptical of learning new things), this is a very, very clear sign that you've outgrown your team it's time to leave your company!
Remember to consider the possibility that they're onto something you've missed. Being part of a team means taking turns learning & teaching.
Seconded. The whole idea that "enterprise development" is somehow distinct from (and usually the implication is 'more important than') normal development really irks me.
If there really is a benefit for using some technology, then you'll need to come up with a considered list of all the pros and cons that would occur if you switched.
Present this list to your co workers along with explanations and examples for each one.
You have to be realistic when creating this list. You can't just say "Saves us lots of time!!! WIN!!" without addressing the fact that sometimes it is going to take MORE time, will require X months to come up to speed on the new tech, etc. You have to show concrete examples where it will save time, and exactly how.
Likewise you can't just skirt over the cons as if they don't matter, your co-workers will call you on it.
If you don't do these things, or come across as just pushing what you personally like, nobody is going to take you seriously, and you'll just get a reputation for being the guy who's full of enthusiasm and energy but has no idea about anything.
BTW. Look out for this particular con. It will trump everything, unless you have a lot of strong cases for all your other stuff:
Requires 12+ months work porting our existing code. You lose.
Of course, "it depends" on the situation. Sometimes DataSets or DataTables are more suited, like if it really is pretty light business logic, flat hierarchy of entities/records, or featuring some versioning capabilities.
Custom object collections shine when you want to implement a deep hierarchy/graph of objects that cannot be efficiently represented in flat 2D tables. What you can demonstrate is a large graph of objects and getting certain events to propagate down the correct branches without invoking inappropriate objects in other branches. That way it is not necessary to loop or Select through each and every DataTable just to get the child records.
For example, in a project I got involved in two and half years ago, there was a UI module that is supposed to display questions and answer controls in a single WinForms DataGrid (to be more specific, it was Infragistics' UltraGrid). Some more tricky requirements
The answer control for a question can be anything - text box, check box options, radio button options, drop-down lists, or even to pop up a custom dialog box that may pull more data from a web service.
Depending on what the user answered, it can trigger more sub-questions to appear directly under the parent question. If a different answer is given later, it should expose another set of sub-questions (if any) related to that answer.
The original implementation was written entirely in DataSets, DataTables, and arrays. The amount of looping through the hundreds of rows for multiple tables was purely mind-bending. It did not help the programmer came from a C++ background attempting to ref everything (hello, objects living in the heap use reference variables, like pointers!). Nobody, not even the originally programmer, could explain why the code is doing what it does. I came into the scene more than six months after this, and it was stil flooded with bugs. No wonder the 2nd-generation developer I took over from decided to quit.
Two months of tying to fix the chaotic mess, I took it upon myself to redesign the entire module into an object-oriented graph to solve this problem. yeap, complete with abstract classes (to render different answer control on a grid cell depending on question type), delegates and eventing. The end result was a 2D dataGrid binded to a deep hierarchy of questions, naturally sorted according to the parent-child arrangement. When a parent question's answer changed, it would raise an event to the children questions and they would automatically show/hide their rows in the grid according to the parent's answer. Only question objects down that path were affected. The UI responsiveness of this solution compared to the old method was by orders of magnitude.
Ironically, I wanted to post a question that was the exact opposite of this. Most of the programmers I've worked with have gone with the custom data objects/collections approach. It breaks my heart to watch someone with their SQL Server table definition open on one monitor, slowly typing up a matching row-wrapper class in Visual Studio in another monitor (complete with private properties and getters-setters for each column). It's especially painful if they're also prone to creating 60-column tables. I know there are ORM systems that can build these classes automagically, but I've seen the manual approach used much more frequently.
Engineering choices always involve trade-offs between the pros and cons of the available options. The DataSet-centric approach has its advantages (db-table-like in-memory representation of actual db data, classes written by people who know what they're doing, familiar to large pool of developers etc.), as do custom data objects (compile-type checking, users don't need to learn SQL etc.). If everyone else at your company is going the DataSet route, it's at least technically possible that DataSets are the best choice for what they're doing.
Datasets/tables aren't so bad are they?
Best advise I can give is to use it as much as you can in your own code, and hopefully through peer reviews and bugfixes, the other developers will see how code becomes more readable. (make sure to push the point when these occurrences happen).
Ultimately if the code works, then the rest is semantics is my view.
I guess you can trying selling the idea of O/R mapping and mapper tools. The benefit of treating rows as objects is pretty powerful.
I think you should focus on the performance. If you can create an application that shows the performance difference when using DataSets vs Custom Entities. Also, try to show them Domain Driven Design principles and how it fits with entity frameworks.
Don't make it a religion or faith discussion. Those are hard to win (and is not what you want anyway)
Don't frame it the way you just did in your question. The issue is not getting anyone to agree that this way or that way is the general way they should work. You should talk about how each one needs to think in order to make the right choice at any given time. give an example for when to use dataSet, and when not to.
I had developers using dataTables to store data they fetched from the database and then have business logic code using that dataTable... And I showed them how I reduced the time to load a page from taking 7 seconds of 100% CPU (on the web server) to not being able to see the CPU line move at all.. by changing the memory object from dataTable to Hash table.
So take an example or case that you thing is better implemented differently, and win that battle. Don't fight the a high level war...
If Interoperability is/will be a concern down the line, DataSet is definitely not the right direction to go in. You CAN expose DataSets/DataTables over a service but whether you SHOULD or is debatable. If you are talking .NET->.NET you're probably Ok, otherwise you are going to have a very unhappy client developer from the other side of the fence consuming your service
You can't convince them otherwise. Pick a smaller challenge or move to a different organization. If your manager respects you see if you can do a project in the domain-driven style as a sort of technology trial.
If you can profile, just Do it and profile. Datasets are heavier then a simple Collection<T>
DataReaders are faster then using Adapters...
Changing behavior in an objects is much easier than massaging a dataset
Anyway: Just Do It, ask for forgiveness not permission.
Most programmers don't like to stray out of their comfort zones (note that the intersection of the 'most programmers' set and the 'Stack Overflow' set is the probably the empty set). "If it worked before (or even just worked) then keep on doing it". The project I'm currently on required a lot of argument to get the older programmers to use XML/schemas/data sets instead of just CSV files (the previous version of the software used CSV's). It's not perfect, the schemas aren't robust enough at validating the data. But it's a step in the right direction. The code I develop uses OO abstractions on the data sets rather than passing data set objects around. Generally, it's best to teach by example, one small step at a time.
There is already some very good advice here but you'll still have a job to convince your colleagues if all you have to back you up is a few supportive comments on stackoverflow.
And, if they are as sceptical as they sound, you are going to need more ammo.
First, get a copy of Martin Fowler's "Patterns of Enterprise Architecture" which contains a detailed analysis of a variety of data access techniques.
Read it.
Then force them all to read it.
Job done.
data-centric means less code-complexity.
custom objects means potentially hundreds of additional objects to organize, maintain, and generally live with. It's also going to be a bit faster.
I think it's really a code-complexity vs performance question, which can be answered by the needs of your app.
Start small. Is there a utility app you can use to illustrate your point?
For instance, at a place where I worked, the main application had a complicated build process, involving changing config files, installing a service, etc.
So I wrote an app to automate the build process. It had a rudimentary WinForms UI. But since we were moving towards WPF, I changed it to a WPF UI, while keeping the WinForms UI as well, thanks to Model-View-Presenter. For those who weren't familiar with Model-View-Presenter, it was an easily-comprehensible example they could refer to.
Similarly, find something small where you can show them what a non-DataSet app would look like without having to make a major development investment.
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I really need to see some honest, thoughtful debate on the merits of the currently accepted enterprise application design paradigm.
I am not convinced that entity objects should exist.
By entity objects I mean the typical things we tend to build for our applications, like "Person", "Account", "Order", etc.
My current design philosophy is this:
All database access must be accomplished via stored procedures.
Whenever you need data, call a stored procedure and iterate over a SqlDataReader or the rows in a DataTable
(Note: I have also built enterprise applications with Java EE, java folks please substitute the equvalent for my .NET examples)
I am not anti-OO. I write lots of classes for different purposes, just not entities. I will admit that a large portion of the classes I write are static helper classes.
I am not building toys. I'm talking about large, high volume transactional applications deployed across multiple machines. Web applications, windows services, web services, b2b interaction, you name it.
I have used OR Mappers. I have written a few. I have used the Java EE stack, CSLA, and a few other equivalents. I have not only used them but actively developed and maintained these applications in production environments.
I have come to the battle-tested conclusion that entity objects are getting in our way, and our lives would be so much easier without them.
Consider this simple example: you get a support call about a certain page in your application that is not working correctly, maybe one of the fields is not being persisted like it should be. With my model, the developer assigned to find the problem opens exactly 3 files. An ASPX, an ASPX.CS and a SQL file with the stored procedure. The problem, which might be a missing parameter to the stored procedure call, takes minutes to solve. But with any entity model, you will invariably fire up the debugger, start stepping through code, and you may end up with 15-20 files open in Visual Studio. By the time you step down to the bottom of the stack, you forgot where you started. We can only keep so many things in our heads at one time. Software is incredibly complex without adding any unnecessary layers.
Development complexity and troubleshooting are just one side of my gripe.
Now let's talk about scalability.
Do developers realize that each and every time they write or modify any code that interacts with the database, they need to do a throrough analysis of the exact impact on the database? And not just the development copy, I mean a mimic of production, so you can see that the additional column you now require for your object just invalidated the current query plan and a report that was running in 1 second will now take 2 minutes, just because you added a single column to the select list? And it turns out that the index you now require is so big that the DBA is going to have to modify the physical layout of your files?
If you let people get too far away from the physical data store with an abstraction, they will create havoc with an application that needs to scale.
I am not a zealot. I can be convinced if I am wrong, and maybe I am, since there is such a strong push towards Linq to Sql, ADO.NET EF, Hibernate, Java EE, etc. Please think through your responses, if I am missing something I really want to know what it is, and why I should change my thinking.
[Edit]
It looks like this question is suddenly active again, so now that we have the new comment feature I have commented directly on several answers. Thanks for the replies, I think this is a healthy discussion.
I probably should have been more clear that I am talking about enterprise applications. I really can't comment on, say, a game that's running on someone's desktop, or a mobile app.
One thing I have to put up here at the top in response to several similar answers: orthogonality and separation of concerns often get cited as reasons to go entity/ORM. Stored procedures, to me, are the best example of separation of concerns that I can think of. If you disallow all other access to the database, other than via stored procedures, you could in theory redesign your entire data model and not break any code, so long as you maintained the inputs and outputs of the stored procedures. They are a perfect example of programming by contract (just so long as you avoid "select *" and document the result sets).
Ask someone who's been in the industry for a long time and has worked with long-lived applications: how many application and UI layers have come and gone while a database has lived on? How hard is it to tune and refactor a database when there are 4 or 5 different persistence layers generating SQL to get at the data? You can't change anything! ORMs or any code that generates SQL lock your database in stone.
I think it comes down to how complicated the "logic" of the application is, and where you have implemented it. If all your logic is in stored procedures, and all your application does is call those procedures and display the results, then developing entity objects is indeed a waste of time. But for an application where the objects have rich interactions with one another, and the database is just a persistence mechanism, there can be value to having those objects.
So, I'd say there is no one-size-fits-all answer. Developers do need to be aware that, sometimes, trying to be too OO can cause more problems than it solves.
Theory says that highly cohesive, loosely coupled implementations are the way forward.
So I suppose you are questioning that approach, namely separating concerns.
Should my aspx.cs file be interacting with the database, calling a sproc, and understanding IDataReader?
In a team environment, especially where you have less technical people dealing with the aspx portion of the application, I don't need these people being able to "touch" this stuff.
Separating my domain from my database protects me from structural changes in the database, surely a good thing? Sure database efficacy is absolutely important, so let someone who is most excellent at that stuff deal with that stuff, in one place, with as little impact on the rest of the system as possible.
Unless I am misunderstanding your approach, one structural change in the database could have a large impact area with the surface of your application. I see that this separation of concerns enables me and my team to minimise this. Also any new member of the team should understand this approach better.
Also, your approach seems to advocate the business logic of your application to reside in your database? This feels wrong to me, SQL is really good at querying data, and not, imho, expressing business logic.
Interesting thought though, although it feels one step away from SQL in the aspx, which from my bad old unstructured asp days, fills me with dread.
One reason - separating your domain model from your database model.
What I do is use Test Driven Development so I write my UI and Model layers first and the Data layer is mocked, so the UI and model is build around domain specific objects, then later I map these objects to what ever technology I'm using the the Data Layer. Its a bad idea to let the database structure determine the design of your application. Where possible write the app first and let that influence the structure of your database, not the other way around.
For me it boils down to I don't want my application to be concerned with how the data is stored. I'll probably get slapped for saying this...but your application is not your data, data is an artifact of the application. I want my application to be thinking in terms of Customers, Orders and Items, not a technology like DataSets, DataTables and DataRows...cuz who knows how long those will be around.
I agree that there is always a certain amount of coupling, but I prefer that coupling to reach upwards rather than downwards. I can tweak the limbs and leaves of a tree easier than I can alter it's trunk.
I tend to reserve sprocs for reporting as the queries do tend to get a little nastier than the applications general data access.
I also tend to think with proper unit testing early on that scenario's like that one column not being persisted is likely not to be a problem.
Eric,
You are dead on. For any really scalable / easily maintained / robust application the only real answer is to dispense with all the garbage and stick to the basics.
I've followed a similiar trajectory with my career and have come to the same conclusions. Of course, we're considered heretics and looked at funny. But my stuff works and works well.
Every line of code should be looked at with suspicion.
I would like to answer with an example similar to the one you proposed.
On my company I had to build a simple CRUD section for products, I build all my entities and a separate DAL. Later another developer had to change a related table and he even renamed several fields. The only file I had to change to update my form was the DAL for that table.
What (in my opinion) entities brings to a project is:
Ortogonality: Changes in one layer might not affect other layers (off course if you make a huge change on the database it would ripple through all the layers but most small changes won't).
Testability: You can test your logic with out touching your database. This increases performance on your tests (allowing you to run them more frequently).
Separation of concerns: In a big product you can assign the database to a DBA and he can optimize the hell out of it. Assign the Model to a business expert that has the knowledge necessary to design it. Assign individual forms to developers more experienced on webforms etc..
Finally I would like to add that most ORM mappers support stored procedures since that's what you are using.
Cheers.
I think you may be "biting off more than you can chew" on this topic. Ted Neward was not being flippant when he called it the "Vietnam of Computer Science".
One thing I can absolutely guarantee you is that it will change nobody's point of view on the matter, as has been proven so often on innumerable other blogs, forums, podcasts etc.
It's certainly ok to have open disucssion and debate about a controversial topic, it's just this one has been done so many times that both "sides" have agreed to disagree and just got on with writing software.
If you want to do some further reading on both sides, see articles on Ted's blog, Ayende Rahein, Jimmy Nilson, Scott Bellware, Alt.Net, Stephen Forte, Eric Evans etc.
#Dan, sorry, that's not the kind of thing I'm looking for. I know the theory. Your statement "is a very bad idea" is not backed up by a real example. We are trying to develop software in less time, with less people, with less mistakes, and we want the ability to easily make changes. Your multi-layer model, in my experience, is a negative in all of the above categories. Especially with regards to making the data model the last thing you do. The physical data model must be an important consideration from day 1.
I found your question really interesting.
Usually I need entities objects to encapsulate the business logic of an application. It would be really complicated and inadequate to push this logic into the data layer.
What would you do to avoid these entities objects? What solution do you have in mind?
Entity Objects can facilitate cacheing on the application layer. Good luck caching a datareader.
We should also talk about the notion what entities really are.
When I read through this discussion, I get the impression that most people here are looking at entities in the sense of an Anemic Domain Model.
A lot of people are considering the Anemic Domain Model as an antipattern!
There is value in rich domain models. That is what Domain Driven Design is all about.
I personally believe that OO is a way to conquer complexity. This means not only technical complexity (like data-access, ui-binding, security ...) but also complexity in the business domain!
If we can apply OO techniques to analyze, model, design and implement our business problems, this is a tremendous advantage for maintainability and extensibility of non-trivial applications!
There are differences between your entities and your tables. Entities should represent your model, tables just represent the data-aspect of your model!
It is true that data lives longer than apps, but consider this quote from David Laribee: Models are forever ... data is a happy side effect.
Some more links on this topic:
Why Setters and Getters are evil
Return of pure OO
POJO vs. NOJO
Super Models Part 2
TDD, Mocks and Design
Really interesting question. Honestly I can not prove why entities are good. But I can share my opinion why I like them. Code like
void exportOrder(Order order, String fileName){...};
is not concerned where order came from - from DB, from web request, from unit test, etc. It makes this method more explicitly declare what exactly it requires, instead of taking DataRow and documenting which columns it expects to have and which types they should be. Same applies if you implement it somehow as stored procedure - you still need to push record id to it, while it not necessary should be present in DB.
Implementation of this method would be done based on Order abstraction, not based on how exactly it is presented in DB. Most of such operations which I implemented really do not depend on how this data is stored. I do understand that some operations require coupling with DB structure for perfomance and scalability purposes, just in my experience there are not too much of them. In my experience very often it is enough to know that Person has .getFirstName() returning String, and .getAddress() returning Address, and address has .getZipCode(), etc - and do not care which tables are involed to store that data.
If you have to deal with such problems as you described, like when additional column breaks report perfomance, then for your tasks DB is a critical part, and you indeed should be as close as possible to it. While entities can provide some convenient abstractions they can hide some important details as well.
Scalability is interesting point here - most of websites which require enormous scalability (like facebook, livejournal, flickr) tend to use DB-ascetic approach, when DB is used as rare as possible and scalability issues are solved by caching, especially by RAM usage. http://highscalability.com/ has some interesting articles on it.
There are other good reasons for entity objects besides abstraction and loose coupling. One of the things I like most is the strong typing that you can't get with a DataReader or a DataTable. Another reason is that when done well, proper entity classes can make the code more maintanable by using first-class constructs for domain-specific terms that anyone looking at the code is likely to understand rather than a bunch of strings with field names in them used for indexing a DataRow. Stored procedures are really orthogonal to the use of an ORM since a lot of mapping frameworks give you the ability to map to sprocs.
I wouldn't consider sprocs + datareaders a substitute for a good ORM. With stored procedures, you're still constrained by, and tightly-coupled to, the procedure's type signature, which uses a different type system than the calling code. Stored procedures can be subject to modification to acommodate additional options and schema changes. An alternative to stored procedures in the case where the schema is subject to change is to use views--you can map objects to views and then re-map views to the underlying tables when you change them.
I can understand your aversion to ORMs if your experience mainly consists of Java EE and CSLA. You might want to have a look at LINQ to SQL, which is a very lightweight framework and is primarily a one-to-one mapping with the database tables but usually only needs minor extension for them to be full-blown business objects. LINQ to SQL can also map input and output objects to stored procedures' paramaters and results.
The ADO.NET Entity framework has the added advantage that your database tables can be viewed as entity classes inheriting from each other, or as columns from multiple tables aggregated into a single entity. If you need to change the schema, you can change the mapping from the conceptual model to the storage schema without changing the actual application code. And again, stored procedures can be used here.
I think that more IT projects in enterprises fail because of unmaintainability of the code or poor developer productivity (which can happen from, e.g., context switching between sproc-writing and app-writing) than scalability problems of an application.
I would also like to add to Dan's answer that separating both models could enable your application to be run on different database servers or even database models.
What if you need to scale your app by load balancing more than one web server? You could install the full app on all web servers, but a better solution is to have the web servers talk to an application server.
But if there aren't any entity objects, they won't have very much to talk about.
I'm not saying that you shouldn't write monoliths if its a simple, internal, short life application. But as soon as it gets moderately complex, or it should last a significant amount of time, you really need to think about a good design.
This saves time when it comes to maintaining it.
By splitting application logic from presentation logic and data access, and by passing DTOs between them, you decouple them. Allowing them to change independently.
You might find this post on comp.object interesting.
I'm not claiming to agree or disagree but it's interesting and (I think) relevant to this topic.
A question: How do you handle disconnected applications if all your business logic is trapped in the database?
In the type of Enterprise application I'm interested in, we have to deal with multiple sites, some of them must be able to function in a disconnected state.
If your business logic is encapsulated in a Domain layer that is simple to incorporate into various application types -say, as a dll- then I can build applications that are aware of the business rules and are able, when necessary, to apply them locally.
In keeping the Domain layer in stored procedures on the database you have to stick with a single type of application that needs a permanent line-of-sight to the database.
It's ok for a certain class of environments, but it certainly doesn't cover the whole spectrum of Enterprise applications.
#jdecuyper, one maxim I repeat to myself often is "if your business logic is not in your database, it is only a recommendation". I think Paul Nielson said that in one of his books. Application layers and UI come and go, but data usually lives for a very long time.
How do I avoid entity objects? Stored procedures mostly. I also freely admit that business logic tends to reach through all layers in an application whether you intend it to or not. A certain amount of coupling is inherent and unavoidable.
I have been thinking about this same thing a lot lately; I was a heavy user of CSLA for a while, and I love the purity of saying that "all of your business logic (or at least as much as is reasonably possible) is encapsulated in business entities".
I have seen the business entity model provide a lot of value in cases where the design of the database is different than the way you work with the data, which is the case in a lot of business software.
For example, the idea of a "customer" may consist of a main record in a Customer table, combined with all of the orders the customer has placed, as well as all the customer's employees and their contact information, and some of the properties of a customer and its children may be determined from lookup tables. It's really nice from a development standpoint to be able to work with the Customer as a single entity, since from a business perspective, the concept of Customer contains all of these things, and the relationships may or may not be enforced in the database.
While I appreciate the quote that "if your business rule is not in your database, it's only a suggestion", I also believe that you shouldn't design the database to enforce business rules, you should design it to be efficient, fast and normalized.
That said, as others have noted above, there is no "perfect design", the tool has to fit the job. But using business entities can really help with maintenance and productivity, since you know where to go to modify business logic, and objects can model real-world concepts in an intuitive way.
Eric,
No one is stopping you from choosing the framework/approach that you would wish. If you are going to go the "data driven/stored procedure-powered" path, then by all means, go for it! Especially if it really, really helps you deliver your applications on-spec and on-time.
The caveat being (a flipside to your question that is), ALL of your business rules should be on stored procedures, and your application is nothing more than a thin client.
That being said, same rules apply if you do your application in OOP : be consistent. Follow OOP's tenets, and that includes creating entity objects to represent your domain models.
The only real rule here is the word consistency. Nobody is stopping you from going DB-centric. No one is stopping you from doing old-school structured (aka, functional/procedural) programs. Hell, no one is stopping anybody from doing COBOL-style code. BUT an application has to be very, very consistent once going down this path, if it wishes to attain any degree of success.
I'm really not sure what you consider "Enterprise Applications". But I'm getting the impression you are defining it as an Internal Application where the RDBMS would be set in stone and the system wouldn't have to be interoperable with any other systems whether internal or external.
But what if you had a database with 100 tables which equate to 4 Stored Procedures for each table just for basic CRUD operations that's 400 stored procedures which need to be maintained and aren't strongly-typed so are susceptible to typos nor can be Unit Tested. What happens when you get a new CTO who is an Open Source Evangelist and wants to change the RDBMS from SQL Server to MySql?
A lot of software today whether Enterprise Applications or Products are using SOA and have some requirements for exposing Web Services, at least the software I am and have been involved with do.
Using your approach you would end up exposing a Serialized DataTable or DataRows. Now this may be deemed acceptable if the Client is guaranteed to be .NET and on an internal network. But when the Client is not known then you should be striving to Design an API which is intuitive and in most cases you would not want to be exposing the Full Database schema.
I certainly wouldn't want to explain to a Java developer what a DataTable is and how to use it. There's also the consideration of Bandwith and payload size and serialized DataTables, DataSets are very heavy.
There is no silver bullet with software design and it really depends on where the priorities lie, for me it's in Unit Testable code and loosely coupled components that can be easily consumed be any client.
just my 2 cents
I'd like to offer another angle to the problem of distance between OO and RDB: history.
Any software has a model of reality that is to some degree an abstraction of reality. No computer program can capture all the complexities of reality, and programs are written just to solve a set of problems from reality. Therefore any software model is a reduction of reality. Sometimes the software model forces reality to reduce itself. Like when you want the car rental company to reserve any car for you as long as it is blue and has alloys, but the operator can't comply because your request won't fit in the computer.
RDB comes from a very old tradition of putting information into tables, called accounting. Accounting was done on paper, then on punch cards, then in computers. But accounting is already a reduction of reality. Accounting has forced people to follow its system so long that it has become accepted reality. That's why it is relatively easy to make computer software for accounting, accounting has had its information model, long before the computer came along.
Given the importance of good accounting systems, and the acceptance you get from any business managers, these systems have become very advanced. The database foundations are now very solid and noone hesitates about keeping vital data in something so trustworthy.
I guess that OO must have come along when people have found that other aspects of reality are harder to model than accounting (which is already a model). OO has become a very successful idea, but persistance of OO data is relatively underdeveloped. RDB/Accounting has had easy wins, but OO is a much larger field (basically everything that isn't accounting).
So many of us have wanted to use OO but we still want safe storage of our data. What can be safer than to store our data the same way as the esteemed accounting system does? It is an enticing prospects, but we all run into the same pitfalls. Very few have taken the trouble to think of OO persistence compared to the massive efforts by the RDB industry, who has had the benefit of accounting's tradition and position.
Prevayler and db4o are some suggestions, I'm sure there are others I haven't heard of, but none have seemed to get half the press as, say, hibernation.
Storing your objects in good old files doesn't even seem to be taken seriously for multiuser applications, and especially web applications.
In my everyday struggle to close the chasm between OO and RDB I use OO as much as possible but try to keep inheritance to a minimum. I don't often use SPs. I'll use the advanced query stuff only in aspects that look like accounting.
I'll be happily supprised when the chasm is closed for good. I think the solution will come when Oracle launches something like "Oracle Object Instance Base". To really catch on, it will have to have a reassuring name.
Not a lot of time at the moment, but just off the top of my head...
The entity model lets you give a consistent interface to the database (and other possible systems) even beyond what a stored procedure interface can do. By using enterprise-wide business models you can make sure that all applications affect the data consistently which is a VERY important thing. Otherwise you end up with bad data, which is just plain evil.
If you only have one application then you don't really have an "enterprise" system, regardless of how big that application or your data are. In that case you can use an approach similar to what you talk about. Just be aware of the work that will be needed if you decide to grow your systems in the future.
Here are a few things that you should keep in mind (IMO) though:
Generated SQL code is bad
(exceptions to follow). Sorry, I
know that a lot of people think that
it's a huge time saver, but I've
never found a system that could
generate more efficient code than
what I could write and often the
code is just plain horrible. You
also often end up generating a ton
of SQL code that never gets used.
The exception here is very simple
patterns, like maybe lookup tables.
A lot of people get carried away on
it though.
Entities <> Tables (or even logical data model entities necessarily). A data model often has data rules that should be enforced as closely to the database as possible which can include rules around how table rows relate to each other or other similar rules that are too complex for declarative RI. These should be handled in stored procedures. If all of your stored procedures are simple CRUD procs, you can't do that. On top of that, the CRUD model usually creates performance issues because it doesn't minimize round trips across the network to the database. That's often the biggest bottleneck in an enterprise application.
Sometimes, your application and data layer are not that tightly coupled. For example, you may have a telephone billing application. You later create a separate application which monitors phone usage to a) better advertise to you b) optimise your phone plan.
These applications have different concerns and data requirements (even the data is coming out of the same database), they would drive different designs. Your code base can end up an absolute mess (in either application) and a nightmare to maintain if you let the database drive the code.
Applications that have domain logic separated from the data storage logic are adaptable to any kind of data source (database or otherwise) or UI (web or windows(or linux etc.)) application.
Your pretty much stuck in your database, which isn't bad if your with a company who is satisfied with the current database system your using. However, because databases evolve overtime there might be a new database system that is really neat and new that your company wants to use. What if they wanted to switch to a web services method of data access (like Service Orientated architecture sometime does). You might have to port your stored procedures all over the place.
Also the domain logic abstracts away the UI, which can be more important in large complex systems that have ever evolving UIs (especially when they are constantly searching for more customers).
Also, while I agree that there is no definitive answer to the question of stored procedures versus domain logic. I'm in the domain logic camp (and I think they are winning over time), because I believe that elaborate stored procedures are harder to maintain than elaborate domain logic. But that's a whole other debate
I think that you are just used to writing a specific kind of application, and solving a certain kind of problem. You seem to be attacking this from a "database first" perspective. There are lots of developers out there where data is persisted to a DB but performance is not a top priority. In lots of cases putting an abstraction over the persistence layer simplifies code greatly and the performance cost is a non-issue.
Whatever you are doing, it's not OOP. It's not wrong, it's just not OOP, and it doesn't make sense to apply your solutions to every othe problem out there.
Interesting question. A couple thoughts:
How would you unit test if all of your business logic was in your database?
Wouldn't changes to your database structure, specifically ones that affect several pages in your app, be a major hassle to change throughout the app?
Good Question!
One approach I rather like is to create an iterator/generator object that emits instances of objects that are relevant to a specific context. Usually this object wraps some underlying database access stuff, but I don't need to know that when using it.
For example,
An AnswerIterator object generates AnswerIterator.Answer objects. Under the hood it's iterating over a SQL Statement to fetch all the answers, and another SQL statement to fetch all related comments. But when using the iterator I just use the Answer object that has the minimum properties for this context. With a little bit of skeleton code this becomes almost trivial to do.
I've found that this works well when I have a huge dataset to work on, and when done right, it gives me small, transient objects that are relatively easy to test.
It's basically a thin veneer over the Database Access stuff, but it still gives me the flexibility of abstracting it when I need to.
The objects in my apps tend to relate one-to-one to the database, but I'm finding using Linq To Sql rather than sprocs makes it much easier writing complicated queries, especially being able to build them up using the deferred execution. e.g. from r in Images.User.Ratings where etc. This saves me trying to work out several join statements in sql, and having Skip & Take for paging also simplifies the code rather than having to embed the row_number & 'over' code.
Why stop at entity objects? If you don't see the value with entity objects in an enterprise level app, then just do your data access in a purely functional/procedural language and wire it up to a UI. Why not just cut out all the OO "fluff"?