This is a very good and open-ended question.
If we are directly interested in the performance, your question basically boils down to a relational vs graph db question which is a widely discussed topic. This gives a short answer to the question without providing much insight. The key point, however, is how inference and reasoning processes work and how they can be realised in a database context.
Focusing on the logical deduction - a process which obtains a logically certain conclusion from a set of premises, it can be viewed as attempting to find new relations (in a graph case, more generally connections) between entities already present in the database. This process typically involves operating on many-to-many or complex relationships as the sought relation between given entities can easily involve multiple attributes (entities can be multiple hops away).
Now for a relational database, querying these types of relations typically requires introducing multiple JOIN tables which hold foreign keys of participating tables. For complex or multiple relations this is often an overkill. Moreover, in the inference context, even for moderate volumes of data a simple input query may require executing thousands subqueries checking specific premises are satisfied.
Now the problem of high-cost joins is inexistent in graph databases as encoding the database in a graph allows to leverage the multi-connectedness of data required during reasoning as the graph structure allows to query complex and many-to-many relationships naturally.
Now when talking about reasoning, a simple graph database is not enough. In order to have a generic inference engine - capable of providing automated query response, it needs to be able to interpret the data unambiguously - a higher level structure needs to be imposed and the semantics of it - the meaning of the structure, need to be defined.
A structured graph database with explicit semantics gives rise to an entity referred to as the knowledge graph which combines a knowledge base in a graph form with a reasoning engine. Failure of providing an explicit structure to the graph either results in limited expressing power or hand-waving/hard-coded inference procedures.
This provides a very basic top-level explanation. Shoot us questions in case of a doubt.