Eventos “OntoQuad”

A native RDF Store Server for Semantic Web

Eventos Semantic Web Toolset

•  One of them is “OntoQuad”: a native RDF Database Management System Server for Semantic Web

•  We develop a wide range of semantic technology instruments, a whole toolset, including: –  Documents Natural Language Processing –  Documents clusterization and classification –  Semantic Storages –  link discovery framework for the Web of Data

OntoQuad: native RDF Store Server for Semantic Web

OntoQuad is cross-platform and can be deployed on different devices:

•  MS Windows x64 (developed on Windows 7)

•  Unix/Linux x64 (tested on Linux CentOS 6.3)

•  Mobile Android (Samsung Galaxy Note II, Google

Nexus 7 etc.)

•  Raspberry Pi Model B rev 2

•  column-oriented storage, key-value index files implemented using B-trees

•  developed with the latest C++ Standard (C++11)

•  Supports triple (SPO) or quad (SPOC) configurations

•  SPARQL 1.1 Query Language and Protocol, and Java (Jena) API

OntoQuad RDF Store - benchmarking

Berlin SPARQL Benchmark (BSBM): Electronic commerce scenarios

For comparison, we tested BSBM “Explore” Use case for: –  Virtuoso 6.1.6, –  Jena TDB (Fuseki 0.2.7) and –  BigData (Release 1.2.2).

All systems were configured to use 22 GB of main memory.

The benchmark machine: –  quad-core Intel i7-3770 CPU with 32 GB of RAM. –  storage is 2x2 TB 7200rpm SATA hard drives, configured as

software RAID 1.

BSBM tests. QMpH for 10 and 100 millions triples

Query Mix per Hour for 10 millions triples dataset

28,847

50,846

79,700

103,212

6,315 12,253

22,407 28,175

12,963 22,954

34,599

14,132 5,866 10,972

19,153 30,857

0

20,000

40,000

60,000

80,000

100,000

120,000

10m, 1 concurrent user 10m, 2 concurrent users 10m, 4 concurrent users 10m, 16 concurrent users

OntoQuad

Virtuoso

Jena TDB

BigData

8,605

15,814

27,009

31,454

5,270

10,270

18,983 22,163

2,466 3,578 5,839

2,855 2,432 4,046 5,430 6,151

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

100m mt1 100m mt2 100m mt4 100m mt16

OntoQuad

Virtuoso

Jena TDB

BigData

Query Mix per Hour for 100 millions triples dataset

BSBM tests. QMpH for 10 millions datasets for Android

Query Mix per Hour for 10 millions triples dataset, Android vs. Linux Server

3177 Query Mix per Hour Database size – 1,72 GB Executable module size - 61 MB

Android Samsung Galaxy Note II: •  16 GB storage, 2 GB RAM •  Quad-core 1.6 GHz Cortex-A9

3,177

6,315

12,963

5,866

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

OntoQuad Android

Virtuoso Jena TDB BigData

10 millions, 1 concurrent user

10 millions, 1 concurrent user

The benchmark Server (for Virtuoso, Jena, BigData): •  quad-core Intel i7-3770 CPU with 32 GB of

RAM •  storage is 2x2 TB 7200rpm SATA hard

drives, configured as software RAID 1 •  All systems were configured to use 22 GB of

main memory

3,177

6,315

12,963

5,866

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

10 millions, 1 concurrent user

OntoQuad Android

Virtuoso

Jena TDB

BigData

RIA LOD Datasets on basis of “OntoQuad”

RIA http://opendata.ria.ru/sparql, SPARQL examples

•  Object types with instances numbers select ?t ?o (count(?s) as ?number) WHERE { ?s a ?t. ?t ?p ?o. FILTER(lang(?o) = "ru") } group by ?t order by desc(?number)

•  Object types with sameAs in LOD datasets select ?l ?o WHERE { ?s <http://www.w3.org/2000/01/rdf-schema#label> ?l. ?s <http://www.w3.org/2002/07/owl#sameAs> ?o.} order by ?o

•  Persons who live in the same city prefix ria: <http://data.ria.ru#> prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> select ?city ?name {?loc a ria:Location. ?loc rdfs:label ?city. ?s a ria:Person. ?s ria:birthPlace ?loc. ?s rdfs:label ?name. } order by ?city

San Francisco Open Data Examples