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Neo4j Spatial at LocationDay 2013 in Malmö
This document discusses using Neo4j-Spatial and OpenStreetMap to work with web map data. It provides an overview of Neo4j-Spatial's capabilities for spatial data including importing, querying, and exporting OpenStreetMap data. Examples are given of using Neo4j-Spatial to find locations near other points, perform routing queries on OSM data, and analyze contributions of individual OSM users.
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- 18. Finding things closeto other things http://blog.neo4j.org/2011/03/neo4j-spatial-part1-finding-things.html
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Editor's Notes
- #2 The purpose of this presentation is to introduce Neo4j Spatial, and two specific projects, the GSoC and OSM Mention Neo Technologies and AmanziTel, but no more We have a product in the market that uses uDig and Neo4j, but felt that our integration was too specific to our needs, and so decided to collaborate with Neo Technologies to produce a more generalized library available as an extension to the database
- #7 KV: Dynomite, Voldemort, Tokyo* BigTable: HBase, Hypertable, Cassandra Document: CouchDB, MongoDB Graph: AllegroGraph, Sones, Neo4j
- #8 The current success and popularity of NoSQL data models has been driven by the internet, and the associated explosion in the volume and interconnectedness of data.
- #9 This example does highlight a few things about semi-structured data, schema-less databases and even opens the conversation for some discussions on performance (implicit indexes through local search, etc.)
- #10 Storage: plugable – dataset, layer, encoder Search: Indexing is currently an R-Tree, but it is possible to plug in any custom mechanism conforming to the interface. Multi-dimensional index Spatial indices (quad-tree, R-tree, kn-tree, SFCs) Composite indices and dynamic indices Lucene