Data Model = Database

http://mikeomatic.net/?p=195

by Harkins • 18 years ago

35 21 18 years ago

mikeomatic.net

tl• 18 years ago

It's probably worth pointing out that the article's title is "Data Model != Database" as in not equal to.

Harkins• 18 years ago

Given that I copied and pasted it, there's a bug in HN.

maxwell• 18 years ago

I guess it's a good idea to screen out exclamation points in general, but this is obviously an edge case that should get through.

shaunxcode• 18 years ago

He makes quite a few valid points and suggests using a business rules engine called "coda server" http://codaserver.com/, does anyone have any experience/impressions with this?

bsaunder• 18 years ago

No, but it's funny that the compatibility pane suggests that since it sits on top of Oracle and MySQL you have access to your data... by integrating your normal apps at the database?

jwilliams• 18 years ago

Not with Coda, but I've used a lot of commercial implementations (ILog, Fair Isaac, Experian) and been pretty impressed.

One of the biggest problems I encountered was testing and change control. With the rules engine you could suddenly change and manipulate things (sometimes on the fly) - that didn't mean that you should....

Retric2• 18 years ago

I think he has worked with badly designed and maintained enterprise systems. If only one system is talking to the database then the Data Model should map directly to the Database, it's only when you have 20 systems each with their own Data Model that all use the same Database that you have the types of problems he is talking about.

Edit: That or you have stupid people building the Database. Remember just because SQL is easy does not make the scema unimportant.

neilc• 18 years ago

Multiple applications talking to one database is the common case.

brentb• 18 years ago

Even in the case of a database that is only used by a single application, there are plenty of circumstances when it's better to interface with an abstract data model rather than the bare database schema.

One reason could be a desire to keep your database (somewhat or totally) normalized, while also being able to make queries against more natural (for the programmer) abstractions. It's rarely the case that all of a given user's information is stored in a single table (and for good reason... read up on normalization (http://en.wikipedia.org/wiki/Database_normalization) if you're not sure why), but it can sure save a lot of programmer time if your data model acts like it's all in a single table.

The case of multiple applications or systems talking to a single database isn't really all that different from a single application talking to a database, unless you only have one database call in your entire application. As soon as you're talking to the database in more than one spot in your code, unless you're careful, you start running into the brittleness/dependency issues described by the author.

Even if you're the only one working on a given application, in three months you'll have little chance of remembering every dependency created by every database interaction in your application. Abstracting things with a data model won't fix all of the issues addressed by the author of the article, but it sure does make it easier to address them.

Retric2• 18 years ago

Systems that do this tend to burn a lot of cycles without the coder having any idea what's going on. For simple CRUD system that can be OK, but making abstractions above the database is dangerous from a performance standpoint.

Edit: There are a lot of DB tools to help you. Adding views let's you keep normalized schema's while simplifying reading data. Triggers can automate logging etc. I often see people using high level data views that end up giving them less power to manipulate data than the DB has.

PS: Why assume the schema is going to suck? Often it does suck, but that should be telling you to change the schema. I mean I know people that can't stand ugly code but they are willing to turn a blind eye to terrible databases.

13ren2• 18 years ago

Databases became an integration point about 30 years ago, when Oracle ported their DB to every platform in sight, and standardized on SQL as a a way to integrate across heterogeneous hardware environments.

I agree with this blog post, but this is clearly a problem that comes up all the time. My question is: what approaches to abstract data models has the industry already developed to deal with these problems of schema change and so on? I have a feeling it's pretty big business.

Also, web services repeat the problem of schema brittleness, because they have a schema... if that changes, it ripples through all the services that use it.

EDIT that is, unless you can automatically regenerate the entire service, based on the schema - this is cool and works for some cases (eg. forms), and it seems to be the direction the industry is headed (as a no-coding solution, with many benefits: no tedium, no errors, no expensive/unruly expert developers).

BTW: the blog author (Mike Arace) is also the developer of the (free) software he's promoting (CodaServer). I have no problem with that, it's an interesting article. Perhaps that's why he didn't mention alternatives. http://18thstreetsoftware.com/aboutus.php

keefe4• 18 years ago

A lot of people (at least at my current employer) would point you to the semantic web and RDF. One of the big focuses is model driven development - defining application state and behavior in an abstract data model (ontology). I think RDF is a pretty good standard for representing abstract data models because it is general (being based on graphs), simple (triple = (subject, predicate, object), and self describing. There is a lot of bleeding edge work in this area and most of it suffers from severe performance problems at the current state of the art.

keefe4• 18 years ago

close paren where appropriate...

fauigerzigerk• 18 years ago

I like RDF for its flexibility, but OWL is very weak. You can't even define very basic constraints that RDBMS schema languages have had for ages. All value constraints on properties have to be constants. So, for example, you cannot state that shipping_date must greater than order_date.

Querying RDF triples within reasonable performance constraints is very hard for the general case. I've tried a lot in that area. You just can't get around the fact that not using upfront knowledge about access paths to define the storage structures means to accept a huge number of joins. However, it's certainly a possibility to encode that knowledge in indexes instead of the logical data model.

Column databases seem to be promising for RDF storage and query.

13ren2• 18 years ago

RDF is a new solution.

What about the old solutions to this old problem? That's what I was asking about.

DanielBMarkham• 18 years ago

Let's see. Stored procs, ORM, web-tiered business-logic, functional code

Use tiers or abstraction to separate changing layers.

I hate to dismiss it as simply a plug for the author's product, but heck, it ain't like this is a new problem. Why buy yet another product to add into the stack? Programming languages and tools are made to solve this kind of stuff as part of their job.

urlwolf• 18 years ago

THere's another solution. Don't use relational dbs, and use some other storage method based on RDF. There are lots of smart people working on making these as fast as possible, and while they will never be as fast as a relational database (for obvious reasons) they may be fast enough for most applications.

olegp• 18 years ago

Do you know of any specific ones? From what I've seen, RDF storage engines currently implemented, such as the various engines in Sesame, are all pretty slow.

I'm doing a bit of work on trying to implement an RDF store on top of HBase - has anyone thought about this and would be interested in throwing ideas around?

TY• 18 years ago

In my experience, wrapping all data manipulation operations in a set of stored procedures usually provides abstraction layer powerful enough to address the issues raised by the author.

In this approach, no application can change data in the underlying tables directly. Change can only be done by calling appropriate stored procedures. This rule is not optional but mandatory and is enforced by database permissions given to the database account used by each application: grant access to stored procedures, deny DML access to the tables.

As an example, if customer name needs to be updated, client applications will call procedure called update_customer_phone (customer_id, new_phone) instead of issuing a direct SQL statement like

update customers set phone = new_phone where customer_id = XXX

There is no need for the application to know that table named customers even exists.

Read access should be provided through views and not to tables directly. Views provide abstraction layer that will insulate applications from underlying table changes.

While this might seem like a lot work, this approach ends up saving a lot of headache in the long run, especially when one database is used by multiple applications.

The main problem with this approach is unfortunately company politics. In many organizations, the only people who can change stored procedures are DBAs or a group of "database developers". The applications themselves are maintained by "application developers". Usually these are separate groups, reporting to different people with different priorities and getting them to work together is often times challenging.

Data Model = Database

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