We do this, the environment varaiable is at the user level, so the user for each environment that runs the SQL agent jobs is different. So on the the dev environment our agent user is something like SQLDev and on the QA environment it is something like SQLQA.
If you are not running from jobs (which I highly suggest doing except on dev while doing actual development), yes you have to change the enviroment variable to the correct one. We have created cmd line scripts to do that easily and placed them on our desktops, so that we can easily switch the environment variables.
I wouldn't want to have 200 data flows in a single package. The time it'd take just to open up and validate would make you old before your time.
EzAPI is fun but if you're new to .NET and SSIS, oh hell no, you don't want that. I think you'll spend far more time learning about the SSIS object model and possibly dealing with COM than actually getting work done.
Since I'm lazy, I'll plug BIML as a free option you didn't list. From an answer on SO https://stackoverflow.com/questions/13809491/generating-several-similar-ssis-packages-file-data-source-to-db/13809604#13809604
- Biml is an interesting beast. Varigence will be happy to sell you a license to Mist but it's not needed. All you would need is BIDSHelper and then browse through BimlScript and look for a recipe that approximates your needs. Once you have that, click the context sensitive menu button in BIDSHelper and whoosh, it generates packages.
I think it might be an approach for you as well. You define your BIML that describes how your packages should behave and then generate them. In the scenario you describe where you make a change and have to fix N packages, nope, you fix your definition of the problem and regenerate packages.
Or if you've gained sufficient familiarity with the framework then use something like EzAPI to go and fix all the broken stuff. Heck, since you've tagged this as 2005, you could also give PacMan a try if you're in need of making mass modifications to existing packages.
SSIS Design considerations
Generally speaking, I try to make my packages focus on solving a single task (load sales data). If that requires 2 data flows, so be it. What I hate inheriting is a package from the import export wizard with many un-related data flows in a single package. Decompose them into something that solves a very specific problem. It makes future enhancements less risky as the surface area is reduced. An additional benefit is that I can be working on loading DimProducts while my minion is dealing with loading SnowflakeFromHell package.
Then use master package(s) to orchestrate the child work flows. I know you're on 2005 but SQL Server 2012's release of SSIS is the cat's pajamas. I love the project deployment model and the tight integration it allows between packages.
TSQL vs SSIS (my story)
As for the pure TSQL approach, in a previous job, they used a 73 step job for replicating all of their Informix data into SQL Server. It generally took about 9 hours but could stretch to 12 or so. After they bought a new SAN, it went down to about 7+ hours. Same logical process, rewritten in SSIS was a consistent sub 2 hours. Easily the biggest factor in driving down that time was the "free" parallelization we got using SSIS. The Agent job ran all of those tasks in serial. The master package basically divided the tables into processing units (5 parallel sets of serialized tasks of "run replicate table 1", table 2, etc) where I tried to divide the buckets into quasi equal sized units of work. This allowed the 60 or so lookup reference tables to get populated quickly and then the processing slowed down as it got into the "real" tables.
Other pluses for me using SSIS is that I get "free" configuration, logging and access to the .NET libraries for square data I need to bash into a round hole. I think it can be easier to maintain (pass off maintenance) an SSIS package than a pure TSQL approach by virtue of the graphical nature of the beast.
As always, your mileage may vary.
Best Answer
CDC doesn't replace the SSIS -> Staging -> Merge route, it just makes the SSIS part easier - the Extraction of ETL. CDC makes this much easier, it's one of the use cases it was designed for. For every change, you get a copy of the row before and after the change, and you can grab a hold of it and then clean it up.
It does have some gotcha's that aren't obvious before you start. 2 big changes that caught me out were:
It also doesn't provide any way to do a full re-sync of the data, it's only ever additive.
I don't think it's possible to answer the question should I do one or the other, the answer (as is often the case) is "It Depends". It's definitely worth investigating though.
Also note, CDC is only available in Enterprise Edition up to SQL 2016 SP1 (when it becomes available in all editions).