Elasticsearch for Geo

When we first decided to build a geocoding solution back in 2015 that would eventually become Addresscloud we evaluated a lot of different technologies before deciding on Elasticsearch.  We wanted to build a geocoding service that was lightning-fast but able to cope with the complex nuances of addresses, Elasticsearch gave us all of this out of the box and we have not looked back.  Five years on this remains an important part of our architecture and as well as geocoding and reverse geocoding we have extended our use to log analytics and more recently geospatial aggregations for visualising insurance exposure hotspots.

I was fortunate to be invited back to the Mapscaping podcast to talk about our experience of using Elasticsearch at Addresscloud, some of the use cases that this excellent software is well-suited to and others where this is less appropriate.  I always enjoy speaking to Daniel and I hope this helps any developers out there getting started with Elasticsearch.

References

• https://medium.com/@yatinadd/going-geospatial-with-elasticsearch-using-geo-points-plus-its-application-b013c638064e
• https://github.com/pelias/pelias
• https://www.elastic.co/maps
• https://www.elastic.co/guide/en/elasticsearch/reference/current/geo-queries.html