Titan vertex centric indices vs Neo4j labels

Question

I was trying to make a comparison between these two technologies when approaching this and I was wondering if any of you already have some experience dealing with any or both of

Answer 1

The difference between the two concepts is the difference between global and local indexing.

As I understand it, Neo4j vertex labels allow you to break up your index space by "categories" of vertices. In this way, a O(log(|V|)) lookup is now an O(log(|V|/c)), where c is the number of categories/labels you have over your vertex set and (the equation) assumes an equal number of vertices in each category. As such, vertex label aid in global index calls as this is a function of V.

Next, Titan's vertex-centric indices sort and index the incident edges of a vertex. The cost to find a particular edge by its label/properties incident to a vertex is O(log(inc(v))), where inc(v) is the size of the incident edge set to vertex v. As such, vertex-centric indices are local indices as this is a function of v.

As I understand it, Neo4j does not support vertex-centric indices. You see this concept currently in Titan, OrientDB, and TinkerGraph (…and RDF stores sort in this manner as well -- via spog pairings). Next, all known graph databases support global indices though, (I believe only Neo4j and OrientDB), support a vertex set partition via the concept of a label.

Again, assuming my assumptions are correct about the use of vertex labels in Neo4j, we are talking about two different use cases — global vs. local indexing. From the perspective of the supernode problem, global indices do not quell the issue of traversing through a large vertex, while this is the sole purpose of the local vertex-centric indices.

You can read about the supernode problem and vertex-centric indices here:
http://thinkaurelius.com/2012/10/25/a-solution-to-the-supernode-problem/