At GraphAware, we live and breathe Neo4j. For three years, we have been helping customers around the world embrace thisamazing technology as a solution to many interesting problems. Mainstream applications of graphs, such as real-timerecommendations, fraud detection, impact analysis, and graph-aided search, have been getting a lot of media attention.
A common question when planning and designing your Neo4j Graph Database is how to handle “flagged” entities. This couldinclude users that are active, blog posts that are published, news articles that have been read, etc.
In the last post of our “Neo4j Modelling for Beginners” series,we looked at bidirectional relationships. In this post, we compare the implications of qualifying relationships byusing different relationship types versus using relationship properties.
Transitioning from the relational world to the beautiful world of graphs requires a shift in thinking about data. Althoughgraphs are often much more intuitive than tables, there are certain mistakes peopletend to make when modelling their data as a graph for the first time. In this article, we look at one common sourceof confusion: bidirectional relationships.