Graph technologies allow modeling of complex relationships and connections through nodes and edges. There are three main layers of graph technologies: graph databases to store graph data, graph analysis frameworks to analyze large graphs, and graph visualization solutions to interact with graphs. Popular tools in each layer include Neo4j and Titan for databases, Giraph and GraphX for analysis, and Gephi and Cytoscape for visualization. Graph technologies are gaining more attention due to their ability to extract insights from connected data.

1. SAS founded in 2013 in Paris | http://linkurio.us | @linkurious
Introduction to the
graph
technologies
landscape.

2. Introduction.
“At Linkurious we believe graph technologies can
have a powerful impact in the way we think about
data and turn it into new products. This small
report is meant to give you a glimpse into the
emerging graph ecosystem. May it inspire you to
join, use or launch graph projects.”
Sébastien Heymann
CEO of Linkurious

3. Father Of
Father Of
Siblings
What is a graph ?
This is a graph.

4. Father Of
Father Of
Siblings
This is a node
This is a
relationship
What is a graph ? / Nodes & relationshipsWhat is a graph : nodes and relationships.
A graph is a set of nodes
linked by relationships.

5. People, objects, movies,
restaurants, music...
Antennas, servers, phones,
people...
Supplier, roads, warehouses,
products...
Supply chains Social networks Communications
Differents domains where graphs are important.
Graphs can be used to
model many domains.

6. Connect people to potential
friends or to new interests.
Graphs technologies
turn data into insights.
Supply chains Social networks Communications
The impact of graphs.
Faster delivery, more robust
distribution network.
Recover from a power outage
faster.

7. A growing interest in
graphs.
Graphs are gaining traction.
In 2014, graph databases were the most popular database technology.

8. Do you know the graph
landscape?
The graph technologies landscape.

9. The three layers of graph technologies.
Graph visualization
Common tools : Cytoscape, Gephi, Keylines, Linkurious, Tom Sawyer
Software
Other solutions : D3.js, Sigma.js, Vivagraph.js
Graph analysis
Common tools : Faunus, Giraph, GraphLab, Graphx
Other solutions : Pregel
Graph databases
Common tools : InfiniteGraph, Neo4j, OrientDB, Sparksee, Titan
Other solutions : Accumulo, Cayley, HBase, HypergraphDB, Sqrrl, YarcData
Store
Three layers of graph
technologies.
Backend
VisualizeAnalyse
Frontend

10. First layer : the graph databases.
InfiniteGraph Neo4j OrientDB Sparksee Titan
License commercial commercial/op
en-source
apache 2.0
license
commercial apache 2.0
license
Website http://www.
objectivity.
com/infinitegraph
http://www.
neo4j.org/
http://www.
orientechnologi
es.
com/orientdb/
http://www.
sparsity-
technologies.
com/
http:
//thinkaurelius.
github.io/titan/

11. InfiniteGraph
Graph database
Website : http://www.objectivity.com/infinitegraph
License : commercial
InfiniteGraph.
Description
InfiniteGraph, brought by Objectivity, is a distributed graph databases that can
handle very large datasets. It was first released in 2010 and has a commercial
license.

12. Neo4j
Graph database
Website : http://www.neo4j.org/
License : commercial/open-source
Neo4j.
Description
Neo4j, the graph database developed by Neo Technology made it easier to
work with graphs. Since the launch of the V1 in 2010, Neo4j garnered a lot of
interest. Its open-source edition makes it very easy for developers to start
experimenting with graph databases. Today, Neo Technology is the leading
graph database with a long list of customer references. It remains focused on
usability with recent releases bringing changes in the ETL process and data
visualization.

13. Description
OrientDB is an Open Source database with the features of both Document and
Graph databases. OrientDB is written completely in Java and can run on any
platform without configuration and installation.
OrientDB
Graph database
Website : http://www.orientechnologies.com/orientdb/
License : Apache 2.0 license
OrientDB.

14. Description
Sparksee (formerly known as DEX) is a proprietary graph database built for
performance. It has a small footprint, is natively available for .Net, C++, Python
and Java. Sparksee mobile is the first graph database available for iOS and
Android.
Sparksee
Graph database
Website : http://www.sparsity-technologies.com/
License : commercial
Sparksee.

15. Description
Titan, an other open-source project has been gaining a lot of attention lately.
Though still in early stage, Titan is an ambitious project. It is a distributed graph
database built to store and query graphs in the hundreds of billions of vertices
and edges.
Titan
Graph database
Website : http://thinkaurelius.github.io/titan/
License : Apache 2.0 license
Titan.

16. A growing need to store
large graphs.
Key tendencies for graph databases.
Here are a few key tendencies for graph databases :
● graph databases are still a small niche within the NoSQL space but they are coming into
their own ;
● choose the right graph database for your particular use case ;
● other big data solutions are sometimes used to store large graphs : Accumulo, HBase ;
● there exist a few integrated products that mix storage capabilities and advanced
functionalities : Sqrrl, YarcData ;

17. Faunus Giraph GraphLab GraphX
License apache 2.0 license apache 2.0 license commercial/open-
source
apache 2.0 license
Website http://thinkaurelius.
github.io/faunus/
http://giraph.
apache.org/
http://graphlab.
com/
https://spark.
apache.org/graphx/
Second layer : the graph analysis frameworks.

18. Description
The team behind the Titan graph database has also released Faunus. Faunus is
a Hadoop-based graph analytics engine for analyzing graphs represented
across a multi-machine compute cluster. It is compatible with HBase,
Cassandra or Hadoop.
Faunus.
Faunus
Graph analysis
Website : http://thinkaurelius.github.io/faunus/
License : Apache 2.0 license

19. Description
Giraph, the Apache project, is an iterative graph processing system built for high
scalability. It is currently used at Facebook to power its famous Graph Search.
At Facebook, Giraph can process a graph with trillions of connections between
people, places, likes and interests in minutes. It is compatible with Hadoop.
Giraph.
Giraph
Graph analysis
Website : http://giraph.apache.org/
License : Apache 2.0 license

20. Description
People interested in Machine Learning can turn to GraphLab to analyse their
graph data. GraphLab was started as an open-source project by Prof. Carlos
Guestrin of Carnegie Mellon University in 2009. Recently it has evolved in a
data science toolbox but remains very useful for graph analytics.
GaphLab.
GraphLab
Graph analysis
Website : http://graphlab.com/
License : Commercial/Open-source

21. Description
Another popular solution for graph computing is Graphx. It is integrated to
Apache Spark, an open-source data analytics cluster computing framework.
GraphX has a built in library of algorithms and include ETL functionalities. It
doesn’t offer the same performances as Giraph but is easier to use.
GraphX.
GraphX
Graph analysis
Website : https://spark.apache.org/graphx/
License : Apache 2.0 license

22. Graph computation is part
of the big data toolset.
Here are a few key tendencies for the graph analysis frameworks :
● most graph databases have their own query language (ex : Cypher for Neo4j and Faunus
for Titan ) ;
● GraphX and Giraph are bringing graph paradigms to HBase, Cassandra and Hadoop ;
● GraphBuilder, an Intel project can help transform tabular data into graphs ;
Key tendencies for graph analysis frameworks.

23. Third layer : the graph visualization solutions.
Cytoscape Gephi Keylines Linkurious Tom Sawyer
Software
License GPL License CDDL,
GPLv3
commercial commercial commercial
Website http://www.
cytoscape.org/
https:
//gephi.
github.io/
http://keylines.
com/
http://linkurio.us https://www.
tomsawyer.
com/home/

24. Description
Another graph visualization solution is Cytoscape. Mostly used by biologists at
first, it has progressively evolved in a general platform for complex network
analysis and visualization. It is desktop-based and is supported by a large
community.
Cytoscape.
Cytoscape
Graph visualization
Website : http://www.cytoscape.org/
License : GPL License

25. Gephi.
Gephi
Graph visualization
Website : https://gephi.github.io/
License : CDDL, GPLv3
Description
Gephi has played a key role in this process. It is an open-source graph
visualization solution. It packs a powerful set of SNA algorithms and
visualization options. Used by a wide community of scientists and data
scientists, it is akin to a “Photoshop for graphs”.

26. Description
KeyLines is a software library for graph visualization. Developed by Cambridge
Intelligence, it is designed to help developers create interactive web applications
around graphs.
Keylines.
Keylines
Graph visualization
Website : http://keylines.com/
License : commercial

27. Description
Graph visualization is going beyond the world of scientists. Linkurious is a
commercial graph visualization solution that aims to democratize graph
visualization. Its interface is designed for the interactive exploration of large
graphs and comes directly with features common in traditional business
intelligence applications (security, user management, etc).
Linkurious.
Linkurious
Graph visualization
Website : http://linkurio.us
License : commercial

28. Description
Tom Sawyer Software sells a collection of software development kits for graph
visualization and analysis. Its products are used by established companies like
NASA and Oracle. It is compatible with ActiveX, C++, Java, and .NET.
Tom Sawyer Software.
Tom Sawyer Software
Graph visualization
Website : https://www.tomsawyer.com/home/
License : commercial

29. Here are a few key tendencies for graph databases :
● traditional graph visualization solutions were targeted at developers and data scientists :
Cytoscape, Gephi ;
● companies like Cambridge Intelligence and Linkurious are making graphs easier to
understand for business people, not just data scientists ;
● a few projects try to integrate the different layers of the graph technologies into complete
products : Dendrite, Linkurious, Tom Sawyer Software ;
Graph visualization
moving to the enterprise.
Key tendencies for graph visualization solutions.

30. Other notable players.
Full stack graph
startups
Data science
platforms

31. Contact us to discuss your projects
at contact@linkurio.us
Conclusion