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I'm working on an app that requires Rooftop level accuracy coupled with very high volumes. The client would prefer to self-host the solution which might not be a bad idea considering our volume and response time requirements.

I'm not seeing how the usual suspects (Google, MapQuest, ...) might help and the geocodes we get from address correction software are inconsistent quality-wise.

Any pointers or suggestions to vendors and/or solutions are appreciated.

FWIW we're currently using PostGIS.

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It is only as good as the data source: We found Yahoo to be most consistent across the board - based on our address locations. We used FME as a solution but had to slow down the requests. – Mapperz May 3 '13 at 14:57
Where are your locations based? US? – Mapperz May 3 '13 at 15:01
Yes, sorry, currently US only. – Mike Summers May 3 '13 at 20:24

2 Answers 2

For geocoding (converting an address to a lonlat), you might consider Nominatim, which uses OpenStreetMap data and runs on PostGIS. I've gotten pretty good accuracy out of it, but it varies depending on region. It can also do reverse geocoding (lonlat -> address).

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I'm not based in the USA, but I've only heard good things about the TIGER geocoder, and it seems to be the best complement with PostGIS. To quote that link:

The goal of this project is to build a fully functional geocoder that can process an arbitrary United States address string and using normalized TIGER census data, produce a point geometry and rating reflecting the location of the given address and likeliness of the location. The higher the rating number the worse the result.

The reverse_geocode function, introduced in PostGIS 2.0.0 is useful for deriving the street address and cross streets of a GPS location.

The geocoder should be simple for anyone familiar with PostGIS to install and use, and should be easily installable and usable on all platforms supported by PostGIS.

It should be robust enough to function properly despite formatting and spelling errors.

It should be extensible enough to be used with future data updates, or alternate data sources with a minimum of coding changes.

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