How to optimize graph traversals in ArangoDB?

Question

I primarily intended to ask this question : "Is ArangoDB a true graph database ?"

But, this question would sound quite offending.

You, peoples at triAGENS, did a really great job in creating a "multi-paradigm" database. As a user of PostgreSQL, PostGIS, MongoDB and Neo4J/Titan, I really appreciate to see an "all-in-one" solution :)

But the question remains, basically creating a graph in ArangoDB requires to create two separate collections : one for edges and one for vertices, thus, as far as I understand, it already means that vertices and related edges are not "physically" neighbors.

Moreover, even after creating appropriate index, I'm facing some serious performance issues when doing this kind of stuff in Gremlin

g.v('an_id').out('likes').in('likes').count()

Which returns a result after ~ 3 seconds (perceived time)

I assumed I poorly understood how Gremlin and Blueprint/ArangoDB worked so I tried to rewrite the same query using AQL :

LET lst = (FOR e1 in NEIGHBORS(vertices, edges, "an_id", "outbound", [ { "$label": "likes" } ] )
    FOR e2 in NEIGHBORS(vertices, edges, e1.edge._to, "inbound", [ { "$label": "likes" } ] )
        RETURN 1
    )
RETURN length(lst)

Which gives me a delay of same order of magnitude.

If I tried to run the same query on a Titan or Neo4j database (with the very same data), queries returns almost immediately (perceived time : <200ms)

So it seems to me that ArangoDB graph features are a "smart graph layer" above a "traditionnal document database" but that ArangoDB is not a "native" graph database.

To confirm this feeling, I transform data to load it in PostgreSQL and run a query (with a multiple table JOIN as you can assume) and got similar (to ArangoDB) execution delays

Did I do something wrong (in AQL query) ?

Is there a way to optimize the database to get better traversal times ?

In PostgreSQL, conceptually, I would mix edge and node and use a CLUSTER clause to physically order data, does something similar can be done in ArangoDB ? (I assume that it would be hard, as it would involve to "interlace" edges and nodes, just an intuition)

Answer 1

i am a Core Developer of ArangoDB. Could you give me a bit more information ob the dimensions of data you are using?

• Amount of vertices
• Amount of edges

Then we can create our own setup with equal dimensions and optimize it.