I have an internal website we use at work built on top of MySQL and
ASP.NET.  Right now the SQL queries are coded as string literals and
the mapping from .NET classes to SQL tables is done more or less
manually as static functions inside the .NET classes.  In short, it's
really not pretty :)

The LINQ to SQL stuff in Visual Studio 2008 would be great to use, but
it's MS SQL only.  Which lead me to this project.  Our internal web
site doesn't have any critical information stored on it, so I don't
really need a bullet proof solution.  I just need something that's
easy to manage, and the GUI editor for LINQ to SQL is very attractive.

Is this project mature enough to actually use for something like
this?  I don't mind working through minor bugs and the like, but I'd
hate to get half way through implementing something and reach some
blocking bug and have to give up.

...

Also, I have a slightly more general question and figure this is as
good a place as any to ask it :)

As the code is set up right now, we can rebuild the entire database
from code if we need to in a couple days (we query various other sites
through whatever APIs they provide).  So the database is more like a
cache of data than anything sacred.

I was thinking of something along the lines of defining the database
schema in the *.dbml file, and using that to create the database if we
needed to.  Which is a bit backwards from what is usually done.  Does
anyone have any suggestions on if this is a sane thing to do?

Basically the process is: Extract information using APIs -> Store that
information in the database -> Query that database -> Use the query
results to draw graphs and issue alerts and the like.

As I said, right now the queries are all done with string literals, so
it's a pain to debug, and the mapping between .NET classes and SQL
classes is more or less manual.  I'd like to set up some nice GUI
schema and use that for everything so there's one and only one place
to update the schema and map it to the various API calls we need to
make to populate the data.
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