First of all (as explained here), relationships are treated as first-class data in a graph database, instead of second-class metadata in a relational database. Data is queryable or discoverable, while metadata is not. You have to learn metadata through other methods, such as taking training courses, reading documentations, reverse-engineering, or data profiling. The more complex a relational database, the more metadata you need to learn before querying for data. For companies with complex business domains, it is very time-consuming and expensive for employees to learn metadata. It is even more expensive to keep metadata-rich employees.
Secondly (as explained here), you need a true graph query language to take full advantage of relationship data. The old-fashioned SQL is just not designed for this purpose. SQL assumes that you already know relationships as metadata. So it expects you to explicitly spell them out in FROM clauses. If you are trying to use SQL to query/discover unknown relationships in a graph database, you are putting the cart before the donkey.
OrientDB is a self-claimed graph database. However, it completely misses the above 2 points. This is evident when it tries to compare itself against a true graph database, Neo4j.
|Complex Domains||Support schemas around graphs, i.e. vertex and edge hierarchies.||Only support "flat" labels for vertices and edges.|
|Query Language||OrientDB's query language is built on SQL. Considering most developers are familiar with SQL, working with OrientDB is just easier.||Neo4j has its own Query Language called "Cypher" which requires training to learn a new language.|
What are "schemas around graphs?" They are METADATA! Neo4j's not supporting schemas is a conscious strategic design decision, not a trade-off between simplicity or capability. Hierarchy is just a tree structure, a specific type of graph. No matter how complex a domain hierarchy is, a graph database can model it natively as data. There is absolutely no need to introduce metadata. Modeling domain hierarchies as metadata instead of data in a graph database is like putting the donkey before a car.
Cypher provides liberating expressiveness for querying graphs. Its advantages over SQL is at the same level as comparing OOP to procedure languages. Criticizing Cypher on the base of developers' familiarity with SQL is like a swordsmith running a negative ad against a gun shop. "Every knight knows how to use a sword. It requires training to use a gun."