Hello Dave, As an addition to <http://librdf.org/using.html>, please feel free to mention Dydra's use of Raptor.
Following our platform upgrade yesterday [1], we are now using libraptor2 to perform all parsing of data import operations (in any serialization format supported by Raptor) for our users, as well as the serving of downloadable export dumps (in the usual RDF formats) of users' repositories. Internally, our data flows are based mostly on N-Triples/N-Quads, for which we have rolled our own custom C library that churns through triples a little faster than libraptor2. (Some 40+% faster, due to an uber-optimized, hand-rolled parser, plus no dynamic memory allocation.) Externally at the interfaces, however, it's now all libraptor2 -- wholly replacing the earlier Ruby-based parsing/serialization pipelines that simply proved too slow for the demands of our customers. Particularly praiseworthy are Raptor's capabilities for autodetecting input serialization formats, which have considerably simplified the implementation of our data imports. Our GitHub fork of libraptor2 is located at <https://github.com/datagraph/raptor>. Time permitting, and provided it'd be welcome, we'd like to eventually contribute back our N-Quads parser implementation, as that would enable us to simply rely on libraptor2 throughout the stack. Cheers, Arto -- Arto Bendiken | [email protected] | http://dydra.com [1] http://blog.dydra.com/2011/09/07/sparql-11 _______________________________________________ redland-dev mailing list [email protected] http://lists.librdf.org/mailman/listinfo/redland-dev
