Addresses / POIS / streets database
We have built a unique and worldwide address, pois, streets, cities, and administrative divisions databases of 500+ millions entries. Available country per country and in CSV Format to simplify things. We use open data from best open datasources : Openstreetmap, Openaddresses, Geonames, Quattroshapes).
Why it is different
You could probably (logicaly) wonder what we got more than Openaddresses, well we do some processing to clean deduplicate and add informations (e.g : the administrative divisions), we consolidate with openstreetmap addresses and cross the several datasets. We do not only concatenate the datasets...for each records of each datasets, we :
- Merge the informations (e.g : for an address, we can take the alternate names, elevation and population of the city from Geonames, the shape and speed limit of the street from Openstreetmap and the house number from openaddresses).
- Deduplicate : a place or address can be present in several dataset, we take care to only keep one
- Consolidate : based on the feedbacks of our cusomers, we add some usefull calculated fields (see below)
- Correct and normalize : sometimes some entry are not entered the right way or are incorrect, we got some algorithm that take care to correct data when it is possible.
So we have a unique and stong database with the best of each datasource.
It is also different because specific fields useful for routing, GPS, navigation, vehicule tracking, and more : length in meter, number of lanes, speed limit, whether the street is toll or not, azimuth at he beginning and at end of the streets (ordinal orientation in degres). Those fields allow to build very cool stuff and get ready very quickly.
Each row of our datasets has an ID and you can import CSV /TSV for instance in a Postgresql relational database, then you can do some request like 'get all streets of a city' or 'addresses in a bounding box'. checkout our integration guide