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Running path-finding algorithms on large datasets is a use case that graph databases are particularly well suited for. While often pathfinding algorithms are used for finding routes using geospatial data, pathfinding is not just about geospatial data — we often use pathfinding graph algorithms with non-spatial data. We could be exploring neural pathways on a graph of the human brain, finding paths connecting different drug-gene interactions, or finding the shortest path connecting two concepts in a knowledge graph.
In this tutorial, you will see how to build a routing web application using the Neo4j graph database, data from OpenStreetMap and OpenAddresses, and Leaflet.js for rendering our web map
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