Build Your Own Aggregator with FeedZcollector

I’ve been playing around a bit over the past week with an application called FeedZcollector, written by brothers Xander and Fred Zelders. FeedZcollector is a Windows application that monitors RSS feeds, adding new items to either a Microsoft Access or MySQL database. FeedZcollector is the retrieval engine behind Feeds4all.com.
I’ve been using the trial version to pull feeds into Access (this free version limits you to 10 feeds; you can purchase versions of the tool that let you work with 25, 100, 1000, or an unlimited number of feeds).
The tool simply pulls down the latest items from the feeds you enter and stores them (title, abstract, URL, time loaded, etc.) in an Access (or MySQL) database. What you do with them from that point forward is up to you. The Zelders purposefully designed the tool to be a component of something larger — but a component that could be used together with other applications.
In my testing, FeedZcollector did its job well, pulling feeds into Access soon after the source site updated the feed. Being able to construct fielded searches, or to augment entries with other data generated by my hypothetical site’s users (tags, times viewed, etc. — anything that could be recorded in a data structure) makes it a powerful back-end tool for repurposing content.
As a die-hard Mac/Unix guy, I wish there were a version of the software that would run in a Unix/Linux environment. However, according to Fred Zelders,

We (Xander and me) are sorry but we have no plans to make versions for Mac OS X or Unix. The reason is the lack of Mac OS X and/or Unix development skills.
There is a possibility however to run FeedZcollector on a Mac (OS X) by installing and running FeedZcollector under Parallels. (I’m running FeedZcollector myself at this very moment on my iMac 20″)

FeedZcollector is a useful foundation for building your own aggregator without having to rely on external, Internet-based, services such as RSSMix or Sphere that provide aggregation services with or without keyword filtering.