This document provides an overview of two graph data models: RDF and Property Graphs. It describes the key components of each model, including triples for RDF and nodes/edges/properties for Property Graphs. It also discusses Apache projects that work with each model like Apache Jena for RDF and Apache TinkerPop, Spark, Giraph and Flink for Property Graphs. Finally, it notes that while the models have different focuses, they could potentially share technologies like storage and query capabilities.

1. Two graph data models
RDF and Property Graphs
Andy Seaborne
Paolo Castagna
andy@a.o, castagna@a.o

2. Introduction
This talk is about two graph data models
(RDF and Property Graphs), example of a
couple of Apache projects using such data
models, and a few lessons learned along the
way.

3. Graph Data Models
➢ RDF
● W3C Standard
➢ Property Graphs
● Industry standard

4. RDF
➢ IRIs (=URIs), literals (strings, numbers, …),
blank nodes
➢ Triple => subject-predicate-object
● Predicate (or property) is the link name : an IRI
➢ Graph => set of triples

5. prefix : <http://example/myData/>
prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
prefix foaf: <http://xmlns.com/foaf/0.1/>
# foaf:name is a short form of <http://xmlns.com/foaf/0.1/name>
:alice rdf:type foaf:Person ;
foaf:name "Alice Smith" ; # ; means “same subject”
foaf:knows :bob .
:alice
foaf:knows
"Alice Smith"
foaf:name
foaf:Person
rdf:type
:bob

6. prefix : <http://example/myData/>
prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
prefix foaf: <http://xmlns.com/foaf/0.1/>
:bob rdf:type foaf:Person ;
foaf:name "Bob Brown" .
"Bob Brown"
foaf:Person
rdf:type
:bob

7. prefix : <http://example/myData/>
prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
prefix foaf: <http://xmlns.com/foaf/0.1/>
:alice rdf:type foaf:Person ;
foaf:name "Alice Smith" ;
foaf:knows :bob .
:bob rdf:type foaf:Person ;
foaf:name "Bob Brown" .
:alice
foaf:knows
"Alice Smith"
foaf:name
foaf:Person
rdf:type
"Bob Brown"
foaf:Person
rdf:type
:bob

8. RDFS
prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>
prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
prefix foaf: <http://xmlns.com/foaf/0.1/>
foaf:Person rdfs:subClassOf foaf:Agent .
foaf:Person rdfs:subClassOf
<http://www.w3.org/2003/01/geo/wgs84_pos#SpatialThing> .
foaf:skypeID
rdfs:domain foaf:Agent ;
rdfs:label "Skype ID" ;
rdfs:range rdfs:Literal ;
rdfs:subPropertyOf foaf:nick .

9. RDF : Access
➢ SPARQL : Query language
➢ Protocol : over HTTP
PREFIX : <http://example/myData/>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
## Names of people Alice knows.
SELECT * {
:alice foaf:knows ?X .
?X foaf:name ?name .
}

10. RDF : Access
➢ SPARQL : Query language
➢ Protocol : over HTTP
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name ?numFriends {
{ SELECT ?person (count(*) AS ?numFriends) {
?person foaf:knows ?X .
} GROUP BY ?person
}
?person foaf:name ?name .
} ORDER BY ?numFriends

11. RDF : Access
➢ SPARQL : Update language
➢ Protocol : over HTTP
PREFIX : <http://example/myData/>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
INSERT DATA {
:bob foaf:name "Bob Brown" ;
foaf:knows :alice
} ;
INSERT { :alice knows ?B }
} WHERE {
:bob knows ?B
}

12. Apache Jena
TLP: April 2012
➢ Involvement in standards
➢ RDF 1.1, SPARQL 1.1
➢ RDF database
➢ SPARQL server
Other RDF@ASF:
➢ Any23, Marmotta, Clerezza, Stanbol, Rya

13. Property Graph Data Model
A property graph is a set of vertexes and edges with
respective properties (i.e. key / values):
➢ each vertex or edge has a unique identifier
➢ each vertex has a set of outgoing edges and a set of incoming edges
➢ edges are directed: each edge has a start vertex and an end vertex
➢ each edge has a label which denotes the type of relationship
➢ vertexes and edges can have a properties (i.e. key / value pairs)
Directed multigraph with properties
attached to vertexes and edges

14. Property Graph: Example
id = 1 id = 2
name = “Alice”
surname = “Smith”
age = 32
email = alice@example.com
...
name = “Bob”
surname = “Brown”
age = 45
email = bob@example.com
...
since = 01/01/1970
...
id = 3
knows

15. Apache Spark: GraphX*
// Creating a Graph
val vertexes: RDD[(VertexId, (String, String))] =
sc.parallelize (Array((1L,("Alice", "alice@example.com")), (2L,("Bob", "bob@example.com"))))
val edges: RDD[Edge[String]] =
sc.parallelize(Array(Edge(1L, 2L, "knows"))
val graph = Graph(vertexes, edges)
...
Example of parallel graph algorithms available:
// Find the triangle count for each vertex
val triCounts = graph.triangleCount().vertices
// Find the connected components
val cc = graph.connectedComponents().vertices
// Run PageRank
val ranks = graph.pageRank(0.0001).vertices
* GraphX is in the alpha stage

16. Property Graphs @ASF
➢ Apache Tinkerpop (incubating)
➢ Apache Spark > GraphX
➢ Apache Giraph
➢ Apache Flink > Gelly

17. Use Case for Graphs
➢ Analytics
● Social networks and recommendation engines
● Data center infrastructure management
➢ Knowledge Graphs
● Happenings: people, places, events
● Customer databases / products catalogues

18. Some Conclusions
➢ Data Graphs are (still) new to many people
➢ RDF emphasizes information modelling
→ Knowledge graphs
→ SQL-like query
➢ Property Graph emphasizes data processing
→ Data capture
→ Graph analytic algorithms
➢ Naive layering of data models leads dissatisfaction
→ Can only mix toolsets by knowing it’s layered
➢ Could share technology
→ Storage, data access, query algebra

19. Thanks and Q&A
?