Graph databases vs. triple stores

Question

What\'s currently the best choice to persist graph-like structures? Graph databases (e.g. Neo4j) or RDF triple stores (e.g. Virtuoso)?

For example, we have the follo

Answer 1

With Virtuoso you have the following working for you:

-- SPARQL, SQL, SPASQL (SPARQL inside SQL), and SQL inside SPARQL support (e.g. for dealing with N-ary relations via magic/function predicates/properties.

-- works as a compact engine (e.g., as exploited via KDE Desktop) or massive DBMS as demonstrated via the live 17 Billion Triples+ LOD Cloud Cache or the smaller DBpedia live instance.

-- includes Full Text indexing and text patterns in SPARQL (via bif:contains) it also included XPath/Xquery (via xcontains)

-- Acid or Non Acid mode ditto Schema-Last when dealing with Property Graph Store

-- Via Transformation Middleware it can pull data from 80+ data sources (includes REST APIs, SOAP services, Hypermedia Resource, ODBC or JDBC accessible relational data sources etc..) and transform into Transient or Persistent Linked Data graphs

-- Linked Data publishing is automatic i.e., post DBMS record creation you have in-built Linked Data Pages that as views into the DBMS. No messing around re. URL-Rewrite rules, 303 redirects or anything like that. InterWeb scale Super Keys just work!

That's it for now :-)

Answer 2

For horizontal scale (thus small to medium sized databases) graph databases like neo4j will currently give better performance for graph traversals. Triplestores are catching up though. The big advantage of a Triple Store compared to a graph database is that data dumps and query language are standardized, which means its a lot easier to move to another product and prevent vendor lock-in.