Herding Data

In the web application I work on, the data in question exists in one of about four phases at any given time, depending on how you draw the distinctions. Most of the work I do is in trying to herd the data through these phases, expose it to some interface for consumption and/or manipulation, then herd it back across again. Yah!

Phase is actually the wrong word. Universe is better. The data has to shift in and out of different universes, each defining its own view of reality. RDBs and OOP come readily to mind. Both are built around basic concerns necessitated by fundamental paradigms in modern computer architecture; the data needs to, 1) be stored on a disk (RDB) and, 2) pulled into RAM and run through the CPU (OOP).

Since both these universes have their own internal data model empire (object model, schema, whatever), you have adapters like JDBC to convert between them. Dancing around the adapter, I believe, is where much of the pull-your-hair-out complexity comes from in writing software. The adapter’s functionality is simple: acquire cnxn, execute stmt, release cnxn. The adapter’s strengths and weaknesses are easy to understand: connections are expensive, network calls introduce latency, certain types of statements hang the DB server. Surrounding it all you have the ever tightening noose of increasing drain on the computer’s resouces as the application gets used.

Greg Reimer/Collapsing the Multiverse

Greg’s perspective is very different from mine, but we seem to be watching the same issues….

Judging by the first half-dozen entries, Greg’s greimblog has a chance to be something special.  I’m rooting for him; hope he can keep it up.

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