The presentation consist of the following, - What is graph DB ? - Why choose Graph DB ? - Types of Graph DB (Based on storage) - Janus Graph Architecture - Janus Graph Basic Terms - Conceptual working of Gremlin Queries. - Setup Janus Graph on local - Some sample queries - Schema and data modelling - Automatic Schema Maker - Index in Janus Graph

1. Graph DB
● What is graph DB ?
● Why choose Graph DB ?
● Types of Graph DB (Based on storage)
● Janus Graph Architecture
● Janus Graph Basic Terms
● Conceptual working of Gremlin Queries.
● Setup Janus Graph on local
● Some sample queries
● Schema and data modeling
● Automatic Schema Maker
● Index in Janus Graph

2. What is Graph DB ?
● Simply Graph DB is the DB to store Graphs.
● This arise a question, what a graph is ?
○ A diagram showing nodes and relations between those nodes.
A simple graph
Vertex / Node
Edge / Relationship

3. Why choose Graph DB ?
● Data and the relationship between the data is increasing.
● Performance
● Flexibility : Auto change in DB model

4. Types of Graph DB’s (Based on storage)
● Native graph storage : Storage that is specifically designed to store and
manage graphs on disk. Eg. TigerGraph, Neo4j
● Relational Storage : Storage that uses a relational model to store the
vertex table and edge table. Eg. GraphX
● Key-Value Store : Storage that uses NoSQL databases like Cassandra,
HBase, etc. e.g. JanusGraph.

5. Janus Graph Architecture

6. Janus Graph Basic Terms
● Vertex / Node
● Edge / Relation
● Property
● Vertex Label
● Edge Label
Marko Josh
Knows
person person

7. Graph Sample

8. Conceptual working of gremlin queries
● g.V().has('person', 'name', within('marko',
'josh')).outE().groupCount().by(label()).next()
Step 1 :

9. Step 2 :
Step 2 :

10. Step 3 :
Step 3 :

11. Output

12. Setup JanusGraph on local
● Download janusgraph distribution from the link :
https://github.com/JanusGraph/janusgraph/releases
● Unzip janusgraph-0.4.0-hadoop2 distribution
● Go to janusgraph-0.4.0-hadoop2
● run ./bin/gremlin.sh

13. Sample queries
● Get all Vertices : g.V()
● Get all Edges : g.E()
● Get Vertices / Edges count : g.V().count(), g.E().count()
● has clause (where clause) : g.V().has(‘name’,’josh’)
● Get vertex / edge with values : g.V().has(‘name’,’josh’).valueMap()
● Limit query : g.V().limit(1)
● Range query : g.V().range(2,4)

14. Schema and Data Modeling
Defining Edge Labels
● knows = management.makeEdgeLabel('knows').multiplicity(MULTI).make();

15. Schema and Data Modeling conn..
Defining Vertex Labels
● person = management.makeVertexLabel('person').make()
Defining Property Keys
● name = management.makePropertyKey('name').dataType(String.class).make();

16. Schema and data modeling conn..

17. Schema and data modeling conn..
Property Key Cardinality
● SINGLE
● LIST
● SET

18. Automatic schema maker
● This functionality let us define the schema automatically while ingesting
vertex or edges.
● By default auto schema maker is enabled. We can disable this by using the
following property
○ Schema.default = none

19. Index in Janus Graph
In general indexes are the used to make our database retrieval fast on the cost
of storage.
There are two types of index in Janus Graph
● Graph Index : An index which is used to make “list operations” fast.
○ Composite
○ mixed
● Vertex centric index : An index which is used to make traversal fast.

20. Resources
● Udemy Course on JanusGraph :
https://www.udemy.com/course/complete-janusgraph-course-for-
beginners/
● JanusGrpah Documentation : https://docs.janusgraph.org/
● Gremlin Practical Guide : https://kelvinlawrence.net/book/Gremlin-Graph-
Guide.html
● Some related videos : https://www.youtube.com/watch?v=-
zj0EckhOS8&list=PL71i5-fJZYaEeCRqd_rWTMvbK8FrF4bwn

21. Thank You
Skype : er.sanil.bagzai
Contact : +91 8817470111