Archive for the ‘Virtuoso’ Category

Non-Adoption of Semantic Web, Reason #1002

Monday, May 13th, 2013

Kingsley Idehen offers yet another explanation/excuses for non-adoption of the semantic web in On Hybrid Relational Databases. Interview with Kingsley Uyi Idehen by Roberto V. Zicari.

The highlight of this interview reads:

The only obstacle to Semantic Web technologies in the enterprise lies in better articulation of the value proposition in a manner that reflects the concerns of enterprises. For instance, the non disruptive nature of Semantic Web technologies with regards to all enterprise data integration and virtualization initiatives has to be the focal point

You may recall Kingsley’s demonstration of the non-complexity of authoring for the Semantic Web in The Semantic Web Is Failing — But Why? (Part 3).

Could it be users sense the “lock-in” of RDF/Semantic Web?

Q14. Big Data Analysis: could you connect Virtuoso with Hadoop? How does Viruoso relate to commercial data analytics platforms, e.g Hadapt, Vertica?

K​ingsley Uyi Idehen: You can integrate data managed by Hadoop based ETL workflows via ODBC or Web Services driven by Hapdoop clusters that expose RESTful interaction patterns for data access. As for how Virtuoso relates to the likes of Vertica re., analytics, this is about Virtuoso being the equivalent of Vertica plus the added capability of RDF based data management, Linked Data Deployment, and share-nothing clustering. There is no job that Vertica performs that Virtuoso can’t perform.

There are several jobs that Virtuoso can perform that Vertica, VoltDB, Hadapt, and many other NoSQL and NewSQL simply cannot perform with regards to scalable, high-performance RDF data management and Linked Data deployment. Remember, RDF based Linked Data is all about data management and data access without any kind of platform lock-in. Virtuoso locks you into a value proposition (performance and scale) not the platform itself. (emphasis added to last sentence)

It’s comforting to know RDF/Semantic Web “lock-in” has our best interest at heart.

See Kingley dodging the next question on Virtuoso’s ability scale:

Q15. Do you also benchmark loading trillion of RDF triples? Do you have current benchmark results? How much time does it take to querying them?

K​ingsley Uyi Idehen: As per my earlier responses, there is no shortage of benchmark material for Virtuoso.

The benchmarks are also based on realistic platform configurations unlike the RDBMS patterns of the past which compromised the utility of TPC benchmarks.

Full Disclosure: I haven’t actually counted all of Kingsley’s reasons for non-adoption of the Semantic Web. The number I assign here may be high or low.

Literature Survey of Graph Databases

Tuesday, February 19th, 2013

Literature Survey of Graph Databases by Bryan Thompson.

I can understand Danny Bickson, Literature survey of graph databases, being excited about the coverage of GraphChi in this survey.

However, there are other names you will recognize as well (TOC order):

  • RDF3X
  • Diplodocus
  • GraphChi
  • YARS2
  • 4store
  • Virtuoso
  • Bigdata
  • Graph partitioning
  • Accumulo
  • Urika
  • Scalable RDF query processing on clusters and supercomputers (a system with no name at Rensselaer Polytechnic)

As you can tell from the system names, the survey focuses on processing of RDF.

In reviewing one system, Bryan remarks:

Only small data sets were considered (100s of millions of edges). (emphasis added)

I think that captures the focus of the paper better than any comment I can make.

A must read for graph heads!