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Cloud-Native Geospatial Analytics Combining Spatial SQL & Graph Data Science

Spatial SQL has become the standard interface for working with geospatial data in tools like PostGIS, SedonaDB, DuckDB, and BigQuery, allowing us to use familiar syntax across transactional systems and also large scale analytics systems backed by distributed compute frameworks like Apache Spark. Meanwhile, Neo4j’s Cypher query language has emerged as the standard for working with graph data allowing us to model, store, and query data as a graph. In this talk we will see how to leverage the best of both of these worlds by seeing how we can combine Spatial SQL and graph data science for geospatial analytics by looking at building a graph of species interactions from field observations, and modeling the physical world as a graph.

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