Addresses, POIs and streets database
We have built a unique and worldwide addresses, POIs, streets, cities, and administrative divisions database. Split by country, available in CSV or SQL format. We use a wide variety of high quality open data sources : Openstreetmap, Openaddresses, Geonames, Quattroshapes.
What makes Gisgraphy stand out ?
You probably wonder how Gisgraphy is different to Openaddresses. Gisgraphy uses a complex set of rules and algorithms to clean, de-duplicate the Openaddresses data and consolidate further data sources like OpenStreetMaps or Geonames. We do not just concatenate the datasets, for each record of each dataset we:
- Merge the information (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).
- De-duplicate : a place or address can be present in several datasets, we take care to only keep one
- Consolidate : based on the feedbacks of our customers, we add some useful calculated fields (see below)
- Correct and normalize : sometimes some entries are not entered the right way or are incorrect, we apply rules to automatically correct and normalize data if possible.
Each datasource has its own strengths and weaknesses. We consolidate multiple datasets to combine their strengths. This results in a unique and comprehensive database with the best of each data source.
|Addresses||Streets||Points of interest||Cities||City shapes|
Gisgraphy database contains some specific fields : length in meters, number of lanes, speed limit, toll information, and the azimuth of the streets (orientation in degrees). Those fields allow to build application as routing, vehicle tracking, and more.
The Database for the entire planet is about 80 Gigo octets compressed and about 450 Giga octets uncompressed.
A list of available Points of interest (POIs) is available on this page
The rows in CSV files got some fields that reference ids of rows in other CSV files, as an SQL table can have a foreign key that references on another column (primary key) in another table. For instance, the street CSV file has a 'cityid' field that references the id field of the City CSV file. So you can use the CSV files to build an SQL relational database and then perform a SQL request like 'get all streets of a city' or 'list addresses in a bounding box'. Check out our integration guide.