RDF: All content tagged as RDF in NoSQL databases and polyglot persistence
Last week I spend some time on implementing the Blueprints interface on top of Datomic. The RDF and SPARQL feel of the Datomic data model and query approach makes it a good target for implementing a property graph. I finished the implementation and all unit tests are passing. Now, what makes it really cool is that it is the only distributed “temporal” graph database that I’m aware of. It allows to perform queries against a version of the graph in the past.
This is the first solution I’m reading about addressing the time dimension in a graph model.
Original title and link: Distributed Temporal Graph Database Using Datomic ( ©myNoSQL)
Patrick Durusau mentioned on his blog a new record set by Franz’s AllegroGraph: 1 trillion RDF triples. This comes only 2 months after the previous Franz’s AllegroGraph record of 310 billion triples.
My first thought was: why is this important? It was one of the few times I’ve found the answer in the PR announcement:
A trillion RDF Statements […] is a primary interest for companies like Amdocs that use triples to represent real-time knowledge about telecom customers. Per-customer, Amdocs uses about 4,000 triples, so a large telecom like China Mobile would easily need 2 trillion triples to have detailed knowledge about each single customer.
Original title and link: 1 Trillion RDF Triples With Franz’s AllegroGraph ( ©myNoSQL)
An interesting semantic triple store data modeling exercise with MongoDB:
In the MongoDB version of my semantic store I take a different approach to storing the basic building blocks of semantic knowledge representation. For starters I decided that typical ABox and TBox knowledge has really quite different storage requirements and that smashing all the complex TBox assertions into simple triples and stringing them together with meta fields only to immediately join then back up whenever needed just seemed like a bad idea from the NOSQL / document-database perspective.