I am really torn right now between using O/R mappers or just sticking to traditional data access. For some reason, every time I bring up O/R mappers, fellow developers cringe and speak about performance issues or how they're just bad in general. What am I missing here? I'm looking at LINQ to SQL and Microsoft Entity Framework. Is there any basis to any of these claims? What kind of things do I have to compromise if I want to use an O/R mapper. Thanks.
This will seem like an unrelated answer at first, but: one of my side interests is WWII-era fighter planes. All of the combatant nations (US, Great Britain, Germany, USSR, Japan etc.) built a bunch of different fighters during the war. Some of them used radial engines (P47, Corsair, FW-190, Zero); some used inline liquid-cooled engines (Bf-109, Mustang, Yak-7, Spitfire); and some used two engines instead of one (P38, Do-335). Some used machine guns, some used cannons, and some used both. Some were even made out of plywood, if you can imagine.
In the end, they all went really really fast, and in the hands of a competent, experienced pilot, they would shoot your rookie ass down in a heartbeat. I don't imagine many pilots flew around thinking "oh, that idiot is flying something with a radial engine - I don't have to worry about him at all". Everyone understood that there were many different ways of achieving the ultimate goal, and each approach had its particular advantages and disadvantages, depending on the circumstances.
The debate between ORM and traditional data access is just like this, and it behooves any programmer to become competent with both approaches, and choose the option that is right for the job at hand.
I struggled with this decision for a long time. I think I was hesitant for two primary reasons. First, O/R mappers represented a lack of control over what was happening in a critical part of the app and, second, because so many times I've been disappointed by solutions that are awesome for the 90% case but miserable for the last 10%. Everything works for select * from authors, of course, but when you crank up the complexity and have a high-volume, critical system and your career is on the line, you feel you need to have complete control to tune every query pattern and byte over the wire. Most developers, including me, get frustrated the first time the tool fails us, and we cannot do what we need to do, or our need deviates from the established pattern supported by the tool. I'll probably get flamed for mentioning specific flaws in tools, so I'll leave it at that.
Fortunately, Anderson Imes finally convinced me to try CodeSmith with the netTiers template. (No, I don't work for them.) After more than a year using this, I can't believe we didn't do it sooner. My team uses Visual Studio DB Pro, and on every check-in our continuous integration build drops out a new set of data access layer assemblies. This handles all the common, low risk stuff automatically, yet we can still write custom sprocs for the tricky bits and have them included as methods on the generated classes, and we can customize the templates for the generated code as well. I highly recommend this approach. There may be other tools that allow this level of control as well, and there is a newer CodeSmith template called PLINQO that uses LINQ to SQL under the hood. We haven't that yet examined (haven't needed to), but this overall approach has a lot of merit.
Jerry
O/RM tools designed to perform very well in most situations. It will cache entities for you, it will execute queries in bulks, it has a very low level optimised access to objects which is way faster than manually assigning values to properties, they give you a very easy way to incorporate variations of aspect oriented programming using modern technics like interceptors, it will manage entity state for you and help resolve conflicts and many more.
Now cons of this approach usually lies in lack of understanding of how things work on a very low level. Most classic problem is "SELECT N+1" (link).
I've been working with NHibernate for 2.5 years now, and I'm still discovering something new about it almost on a daily basis...
Good. In most cases.
The productivity benefit of using an ORM, will in most case outweigh the loss of control over how the data is accessed.
There are not that many who would avoid C#, in order to program is MSIL or Assembly, although that would give them more control.
The problem that i see with a lot of OR mappers is that you get bloated domain objects, which are usually highly coupled with the rest of your data access framework. Our developers cringe at that as well :) It's just harder to port these object to another data access technology. If you use L2S, you can take a look at the generated code. It looks like a complete mess. NHibernate is probably one of the best at this. Your entities are completely unaware of your data access layer, if you design them right.
It really depends on the situation.
I went from a company that used a tweaked out ORM to a company that did not use a ORM and wrote SQL queries all the time. When I asked about using an ORM to simplify the code, I got that blank look in the face followed by all the negatives of it:
Its High Bloat
you don't have fine control over your queries and execute unnecessary ones
there is a heavy object to table mapping
its not dry code because you have to repeat your self
on an on
Well, after working there for a few weeks, I had noticed that:
we had several queries that were almost identical, and alot of times if there was a bug, only a handful would get fixed
instead of caching common tables queries, we would end up reading a table multiple times.
We were repeating our selves all over the place
We had several levels of skill level, so some queries were not written the most efficiently.
After I pointed most of this out, they wrote a "DBO" because the didn't want to call it an ORM. They decided to write one from scratch instead of tweaking out one.
Also, alot of the arguments come from ignorance against ORM's I feel. Every ORM that I have seen allows for custom queries, and even following the ORM's conventions, you can write very complex and detailed queries and normally are more human readable. Also, they tend to be very DRY, You give them your schema, and they figure the rest out, down to relationship mapping.
Modern ORM's have a lot of tools to help you out, like migration scripts, multiple DB types accessed to the same objects so you can leverage advantages of both NOSQL and SQL DB's. But you have to pick the right ORM for your project if your going to use one.
I first got into ORM mapping and Data Access Layers from reading Rockford Lhotka's book, C# business objects. He's spent years working on a framework for DAL's. While his framework out of the box is quite bloated and in some cases, overkill, he has some excellent ideas. I highly recommend the book for anyone looking at ORM mappers. I was influenced by his book enough to take away a lot of his ideas and build them into my own framework and code generation.
There is no simple answer to this since each ORM provider will have it's own particular pluses and minuses. Some ORM solutions are more flexible than others. The onus is on the developer to understand these before using one.
However, take LinqToSql - if you are sure you are not going to need to switch away from SQL Server then this solves a lot of the common problems seen in ORM mappers. It allows you to easily add stored procedures (as static methods), so you aren't just limited to generated SQL. It uses deferred execution, so that you can chain queries together efficiently. It uses partial classes to allow you to easily add custom logic to generated classes without needing to worry about what happens when you re-generate them. There is also nothing stopping you using LINQ to create your own, abstracted DAL - it just speeds up the process. The main, thing, though is that it alleviates the tedium and time required to create basic CRUD layer.
But there are downsides, too. There will be a tight coupling between your tables and classes, there will be a slight performance drop, you may occasionally generate queries that are not as efficient as you expected. And you are tied in to SQL Server (though some other ORM technlogies are database agnostic).
As I said, the main thing is to be aware of the pros and cons before pinning your colours to a particular methodology.
Many developers seem to be either intimidated or a bit overwhelmed when an application design requires both procedural code and a substantial database. In most cases, "database" means an RDBMS with an SQL interface.
Yet it seems to me that many of the techniques for addressing the "impedance mismatch" between the two paradigms would be much better suited to an ISAM (indexed-sequential access method) toolset, where you can (must) specify tables, indexes, row-naviagation, etc. overtly - exactly the behavior prescribed by the ActiveRecord model, for instance.
In early PC days, dBASE and its progeny were the dominant dbms platforms, and it was an enhanced ISAM. Foxpro continues this lineage quite successfully through to today. MySQL and Informix are two RDBMSs that were at least initially built on top of ISAM implementations, so this approach should be at least equally performant. I get the feeling that many developers who are unhappy with SQL are at least unconsciously yearning for the ISAM approach to be revived, and the database could be more easily viewed as a set of massively efficient linkable hyper-arrays. It seems to me that it could be a really good idea.
Have you ever tried, say, an ORM-to-ISAM implementation? How successfully? If not, do you think it might be worth a try? Are there any toolsets for this model explicitly?
Maybe Pig Latin is what you want? According to this article
http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=693D79B5EFDC0452E1C9A87D1C495D4C?doi=10.1.1.124.5496&rep=rep1&type=pdf :
"Besides, many of the people who ana-
lyze this data are entrenched
procedural programmers, who find the
declarative, SQL style to be
unnatural. The success of the more
procedural map-reduce programming
model, and its associated scalable
implementations on commodity hard-
ware, is evidence of the above.
However, the map-reduce paradigm is
too low-level and rigid, and leads to
a great deal of custom user code that
is hard to maintain, and reuse. We
describe a new language called Pig
Latin that we have designed to fit in a
sweet spot between the declarative
style of SQL, and the low-level,
procedural style of map-reduce."
There are certainly times and places where ISAM provides the services needed by the application with less cost and overhead than a full-blown SQL DBMS. One downside of an ISAM mechanism is that there isn't necessarily a system catalogue to describe the data; another is that generally there are few user-friendly tools to get at the data. These are both places where the RDBMS provides considerable advantage. The best ISAM (or similar) systems provide transaction support - even XA transactions, sometimes.
Where you need to do complex joins and computations (aggregates, for example), the work done by the DBMS provides huge benefits. Where all you need is access to records, then ISAM could be beneficial.
Security tends to be harder to enforce with an ISAM-based system than with a DBMS. Also, you need to worry about integrity of the files in case of a crash. Most DBMS use a two-process architecture (DBMS client in a separate process from the DBMS server), which provides resilience in the face of the client crashing (or the client PC being turned off). You also have to worry about backup and restore - a competent DBMS has systems in place for providing a coherent backup of a database while the database is in use; it is not clear that ISAM systems would provide that level of integrity.
Overall, given a suitable ISAM mechanism, there would at least sometimes, maybe often, advantages to using an ISAM mechanism in an ORM system instead of a full RDBMS.
I implemented an ORM-to-isam library back in the 1990s that enjoyed some (very) modest success as shareware. I largely agree with what you say about the virtues of ISAMs and I think it better to use an ISAM when building an ORM layer or product if you are looking only for flexibility and speed.
However, the risk that you take is that you'll lose out on the benefits of the wide range of SQL-related products now on the market. In particular, reporting tools have evolved to be ever more tightly integrated with the most popular SQL packages. While ISAM product vendors in the 1990s provided ODBC drivers to integrate with products like Crystal Reports, it seemed, even then, that the market was trending away from ISAM and that I would be risking obsolescence if I continued using that technology. Thus, I switched to SQL.
One caveat: it has been nearly a decade since I was playing in the ISAM sandbox so I cannot purport to be up on the latest ISAM tools and their solutions to this problem. However, unless I was convinced that I was not going to be trapped without reporting tools support, I would not adopt an ISAM-based ORM regardless of its virtues. And that doesn't even cover the other tools available for SQL-based development!
I did my share of dBase, Clipper and FoxPro. However I believe the relational model provided by SQL is infinitely more powerful and useful, and products like Oracle and SQL Server deserve their success in the marketplace.
I'm always surprised why people make such a big deal of creating a mapping layer for the ~80-90% of the cases and writing 10-20% of custom SQL to deal with complex queries (mostly reports) and batch data movement. I must be doing something really good or something really silly by adopting the DAL/DAO model, given the level of hatred against hibernate, active record, etc. - vide Vietnam discussion from earlier.
Multivalue database anyone? (aka Pick) Think XML without the tags. They predate RDBMS by at least a decade, and still going strong if you know where to look.
If you know exactly what you want to do with your data and how you want to do that, pick ISAM. You will be happy because you will have structured your indexes to serve your exact needs. Know upfront that if your needs change, you will want to change your indexing. Data access will be blazing fast.
If you are not sure what uses the data will be put to, or you know your data needs will change a lot over time, pick SQL. You will have the flexibility of ad hoc queries, quick reporting turnaround, data mining, etc.
Both types of databases have matured over the years. Both can have robust servers with live backup, transactions, security, metadata, etc.
Old question, but interesting discussion. The concepts of ISAM are important, the additional features that we're provided in today's RDBMSs (as discussed i.e. backup, consistency, security, metadata) offer us signficant benefits.
With the NoSQL craze (yes I said it...craze) it doesn't mean that we can't model ISAM-like access inside the RDBMS. You'll be sure I'm gonna push off as much logic to the DB as I possibly can, but there are times like "traditional" data gridding/multi-dimensional data interpolation where I'll traverse all necessary records via my own logical index.
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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"?