Graph databases are the NoSQL of this half decade. Move cautiously. Just because you conceptualize it in your mental model does not mean you need a graph database. Further, recognize most (all?) implementations are not yet as performant or scalable as traditional data storage solutions.

Design your data schema first, then design your queries and finally your data lifecycle pipeline. Run some estimates on the order of magnitude for inserts, query rates, query types and storage sizes - then compare those numbers to the real-world perf of the various graphdb solutions. In general, compared to more typical solutions, you have more expensive inserts, query costs and storage sizes in exchange for more expressive queries. There aren't many application where those cost tradeoffs make sense.

Source: Twice now (2012 and 2018) I've reviewed available graphdbs for storage of enterprise security data when doing the initial platform technology selection. Both times the team fell back onto more traditional approaches.