I support this proposal - great idea, something that's been missing in Spark world. I'm a data architect working primarily in banking, many years of designing and tuning relational database systems, and more recently, wBig Data solutions, often including integration of old and new technologies. The graph database model is becoming more and more recognised and present in the world of finance. The idea of being able to take a property graph view over dataframes and run graph queries makes a lot of sense from the integration point of view as we want to use graph databases/services alongside existing investments in the Spark ecosystem (typically deployed on Hadoop clusters, typically implementing relational stuff). I can see use cases (relational-meets-graph) in my world, specifically for completeness/availability calculation dependency graphs, metadata and data management in the space where enterprise architecture meets BCBS239 (taxonomy, provenance, lineage), plus of course unauthorised trading, fraud detection, all that. An additional bonus here is that Cypher seems like a good choice in light of its spread beyond Neo and its contribution to the future official ISO standard Graph Query Language.
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