Agile Data Structures

I’ve been working with a start-up that is going to need a very large database. It is an obvious cloud application, and is going to require a lot of modeling. Also, it shouldn’t be too surprising that every meeting we have changes the very nature of the database and the applications it will support. Now the Agile folks are definitely not surprised, and they claim to have just the answer: Agile everything.

OK, I like Agile philosophies (Cf. my post “Thoughts on Agile and Scrum”), but the practicality of constantly changing the schema of a huge database with many applications banging on it seems daunting, especially in a cloud environment. In addition, a start-up doesn’t have the luxury of simultaneously updating each application with every schema change; hence, I decided to see if some form of database refactoring could be designed into the system from the beginning. The goals would be not only to address continual specification and design changes, but more importantly to keep the individual application development teams on paths that allowed them to react to these changes naturally as their current work tasks (“sprints”) completed, and they had the opportunity to seriously contemplate these changes and how to address them.

I’ve already started plowing through many of Scott Ambler’s writings, cf. www.agiledata.com, www.ambysoft.com, and www.agilemodeling.com. He writes well, and it is as good a starting point as I can find.

Thus I’m going to make a series of blog entries as I think through the pros and cons of the Agile tools and data techniques out there – especially in the context of developing a large database on the cloud (or maybe I should say “on a cloud.”) Stay tuned.

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