I don’t think there is, but TigerGraph uses node-based sharding like neo4j et al, (rather than predicate based), so even if you use their affinity-based partitioning (which they recommend against) I expect they will have cases where large data sets in a distributed environment cause excessive network communications when trying to navigate links among many nodes during query processing.
In contrast (and I think uniquely) Dgraph uses predicate-based sharding, which allows a query to execute using a fixed number of network calls between nodes (about equal to query join count). See the “developers in sf who use vim” example here: Database sharding: How to scale a graph database - Dgraph Blog .