I'm working on one specific case which involves multilayer networks and therefore considering to use Neo4j instead of the mostly unstandardized software solutions like MuxViz, Py3plex, etc.
For more info please visit https://link.springer.com/article/10.1007/s41109-019-0203-7/tables/1
The mentioned packages includes specific algorithms which can calculate centrality measures on multilayer networks, taking into account all of the layers, not only one. That being said, my scenario could resemble something like this:
A.) Trade networks - countries are nodes, links are traded goods, date is a temporal value. That way for example i can have five networks with five different goods, one network for each year;
B.) Communication networks - people are nodes, links are channels of communication, date is also a temporal value. For example, i have three networks (calls, messages, e-mails).
Conclusively, Neo4j can easily calculate centrality measures for each network layer, but the idea is to take all layers into account at once.