Graph Database for Collaborative Communities - Community-Built Databases: Research and Development - page 218

Table 9.2 Graph query languages-1-
G

G+
GraphLog

Hyperlog QGraph GOOD Kalpan HNQL

Basic unit Nodes/

edges

Nodes/
edges

Hypernode Nodes/
edges

Nodes/
edges

Nodes/
edges

Hypernode

Data model Graph Graph Hypernode Graph GOOD Semantic

graph

Hypernode

Language style Graphical Graphical Graphical Graphical Graphical Semantic Formal

Pattern + + Rules + + +

Update query + + + + + +

Implementation + + + + +

Path +/ + +/ +/ +/ + +/

Neighborhood + +/ +/ + +/

Diameter +

Distance between
nodes

+

Table 9.3 Graph query languages-2-
Lorel

GOQL SOQL GraphDB GraphQL LDM Gram G-Log

Basic Unit Object Nodes/

edges

Group/
path

Nodes/
edges

Graph Tuple Nodes/

edges

Nodes/
edges

Data Model OEM Graph Graph Graph Graph LDM Gram G-Log

Query style SQL-like SQL-like SQL-like SQL-like SQL-like Formal Formal Formal

Pattern + + + +

Update query + + +

Implementation + + + + +

Path + + + + + + +/

Neighborhood +/ +/ +/ +/ + +/ +/

Diameter +/

Distance between
nodes

+/ +

characteristics of a social network, even those designed for social networks (e.g.,
SoQL). We summarize the main characteristics of the previous languages in
Tables 9.2 and 9.3 . We put (+) where the language proposes an explicit definition
for the characteristics, (

) if not, and (+/ ) where it tries to define it indirectly.

These two tables show that:

l Many query languages use pattern to facilitate the information search process
especially graphical languages such as Good, Qgraph, and G.
l Most languages provide operator or techniques to find path. Nevertheless,
graphical languages do not determine path by direct operation.
l The neighborhood characteristic is not well processed by existing languages.
l Graph characteristics based on calculations such as diameter or distances
between nodes are treated only by G+ and GraphLog.

In practice, users prefer graphical languages because they are easy to use.
Moreover, graphical query languages for a graph model are unable to obtain
information about communities. Languages designed for a social network such as
SOQL are based on SQL and can be applied only on simple graphs.