What is a

Graph Database?

Graph Theory

• Nodes and (un/directed) edges
• Both can have properties

OS Property Graph DB

(with spatial support)

• ArangoDB
• Neo4j
• OrientDB
• Titan (through Cassandra)

Semantic Web

• Triples
  • (subject)-predicate->(object)
• Standards: OWL, RDF, SPARQL

OS Triplestores

(with spatial support)

• Blazegraph
• GraphDB (ontotext)
• KiWi (Sesame) > PostGIS backend
• Virtuoso

Routing

• Create a routable network
• Finding shortest path between nodes
• Finding nearest edge / node to start point

How we did it

• Streets and intersections as nodes
• Mapping weights to edges
• Implemented using Neo4j incl. spatial in embedded mode
• Dikjstra & A-Star Algorithmus

Results

• Routing works and it's easy to set up
• Slower than with SotA routing engines
• KNN is a lot slower compared to PostGIS

Meta data catalogue

• Connect heterogenous data source
• Store meta data as a graph
• Persist matches through additional edges

3D

2D

GIS

BIM

GIS

...

...

Scenario

• Data of the Botanical Garden of Berlin maintained in different domain-specific systems
• Loads of CAD data which had to be georeferenced
• Research project ArcoFAMA

How we did it

• Migrating CAD data to Postgres using ETL tools
• Meta data graph stored in Neo4j
• Web front end for browsing the graph

Results

• Meta data graph is easy to build and to extend
• Fast enough because it does not store the real data
• Spatial queries done with GeoTools, not Neo4j spatial
• Semantic Web tools / DBs better suitable to this idea

Data Modelling

When using a

relational DBMS

• Many tables = many joins
• Not so flexible with ADEs
• If it's only for storage why not schemaless?

How we did it

Agoub, A.; Kunde, F.; Kada, M. (2016): Potential of Graph Databases in Representing and Enriching Standardized Geodata.

UML

XSD

XML

Jsonix

Binding

[
 Node {id,parent..},
 Node {id,parent..},
 Node {id,parent..},
 .
 .
 Node {id,parent..}
] 

Nodes & Edges

Results

Missing geometry types

Schema validation

UML

XSD

XML

Jsonix

Binding

[
 Node {id,parent..},
 Node {id,parent..},
 Node {id,parent..},
 .
 .
 Node {id,parent..}
] 

Graph DBs are schemaless. No extra layer for validation.

Schema validation

OGC

XSD

XML

Jsonix

Binding

Model

Validation

JSON

Schema

Multi-model

(Documents, Graph)

Foxx

Queries are easy

Neo4j - Cypher

MATCH 
  (b:Building {B.id:?}) -[:REL*]-> (m)
RETURN 
  b,m

ArangoDB - AQL

FOR user IN Buildings
FILTER Building.id == ? 

... compared to

PostgreSQL (3DCityDB) - SQL

SELECT sg.*, tp.*, sd.*, a.* 
  FROM building b
  JOIN thematic_surface ts 
    ON ts.building_id = b.id
  JOIN surface_geometry sg 
    ON sg.root_id = ts.lod2_multi_surface_id
  LEFT JOIN textureparam tp
    ON tp.surface_geometry_id = sg.id
  LEFT JOIN surface_data sd 
    ON sd.id = tp.surface_data_id
  LEFT JOIN appear_to_surface_data ats
    ON ats.surface_data_id = sd.id
  LEFT JOIN appearance a 
    ON a.id = ats.appearance_id
  WHERE b.id = ?