A better release announcement, which I wrote over on the Labs Weblog:
MetaCarta Labs is proud to announce the release of FeatureServer, an open source, Python based RESTful feature server.
FeatureServer allows you to store points, lines, and polygons in a number of backends, and get the data out all at once or one piece at a time. You can get the data out as KML, JSON, GeoRSS, GML/WFS or even as HTML.
FeatureServer is primarily designed as a lightweight vector feature storage companion to the new OpenLayers vector capabilities.
A demo of FeatureServer in OpenLayers is available at the FeatureServer Demo page. You can see features from this demo in:
FeatureServer is the first project we’ve released under our copyright-only open source license, a move designed to protect both MetaCarta and project contributors. We’re moving forward with getting this license approved by OSI, and plan to release future open source software under this license.
I’ve been looking forward to this for a long time, and am looking forward to demoing it for people at Where 2.0. I think that FeatureServer really is the first step forward in the world of interacting with geodata on a feature level rather than a giant-database level. Per-feature interaction — view, update, delete — as well as easy-to-use attribute querying are both huge boons when working with lots-o-data: instead of loading 700,000 features, or even just loading features based on a bounding box, you can talk about a feature based on its unique identifier.
It also makes a really great translator — for example, it makes it possible to load up your Flickr photos as a WFS server which you can drop into OpenLayers. No need to depend on the external interfaces: anything which provides a geospatial data API can be converted to a FeatureServer datasource.
The ability to read in GeoRSS and KML are great from the point of view of an aggregator: simply pipe the output of a curl GeoRSS download into a FeatureServer upload, and you’ve got a GeoRSS post collector.
There’s a ton of possibilities, and I’m looking forward to helping people explore them now that the software is available and open source.