triplestore

Ease of installation/use is the most important factor here - not performance. Small is OK as large datasets are not expected. I'd also recommend sesame , its lightweight, pretty easy to install, and provides good performance for small datasets. Query performance is far better with Sesame 1.2.x than Sesame 2.x because of the addition of context support to the 2.x series. I've tested sesame installation/deployment with tomcat, resin, and jetty, and it worked easily with all of them. I don't recommend the bindings to RDBMS components such as Postgres or MySQL, at least in the 1.x series,

I have a question about the deletion of elements from a triplestore (in my case a Virtuoso) using SPARQL. I have stored the following elements in a graph: @prefix xy: <http://purl.oclc.org/xy/xy#> . @prefix ssn: <http://purl.oclc.org/NET/ssnx/ssn#> . <point> a xy:Point ; xy:value "10" ; ssn:observationResultTime <Rs_b8d4ae44-6083-4140-b4e3-11fcf38a53c8> ; ssn:observationSamplingTime <St_b8d4ae44-6083-4140-b4e3-11fcf38a53c8> ; ssn:observedBy <SensorID-b8d4ae44-6083-4140-b4e3-11fcf38a53c8> . As you can see I have one xy:Point, which has some properties. In my database I have stored dozens of

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 following use case: the weakly connected graph (similar to the one of scholarly papers in a collection) with nearly 10M nodes; quite rare updates; critical operations: retrieving particular sub-graphs, updating nodes in a given sub-graph, re-computing link analysis measures (e.g. HITS or PageRank) after updating some nodes. Providing the standard API to query the data for third party applications (a la Facebook's or Twitter's) is