Life goes on, however. Research and development, product releases, and new features never stop. Case in point – we’ve seen a few significant updates from graph database vendors in the last couple of months.
Graph databases and analytics are getting ever more accessible and relevant, and vendors seem to be going through a virtuous circle of innovation. DataStax has unified graph with native Cassandra data model in DSE 6.8, TigerGraph 3.0 brings no code data migration and visual querying, and Neo4j has released a BI connector and Neo4j for Graph Data Science.
Read more: https://dzone.com/articles/knowledge-graphs-power-scientific-research-and-bus
Keywords: Amy E. Hodler • Amy Hodler • GDS • graph data science • Graph Machine Learning