The document discusses a project analyzing social networks using a graph database. It introduces the three project members and defines what a graph is - a collection of nodes and relationships. It then discusses properties of graph databases, why the Neo4j graph database was chosen, its Cypher query language, and compares graph and relational databases. Execution times are faster for graph databases on large connected datasets. Applications discussed include product recommendation and finding shortest paths.

1. Project Mentor: Mrs. Manisha Gahirwal
Project Members:
Rahul Anwani(03)
Akshaykumar Oswal(19)
Srinivas Ravi(48)
Social Networking Analysis using
Graph Database

2. Social Network is a highly connected data

3. What is Graph?
A graph is a collection of vertices and edges.
It is a set of fundamental units called NODES and the
RELATIONSHIPS that connect these nodes.
Data is stored in both Nodes as well as Relationships

5. Properties of Graph Databases
1. The underlying storage
2. The processing engine

6. Why Neo4j?
• reliable
• durable and fast
• massively scalable
• highly-available
• expressive
• fast
• simple

7. Cypher Query Language
• declarative graph query language
• what to retrieve
• Expressions
• Identifiers
• Operators
• Pattern
• Labels
Building blocks of CQL

8. Structure
• MATCH
• RETURN
• WHERE
• LIMIT
• ORDER BY
• CREATE
• REMOVE
• DELETE

9. Relational Database System Graph Database System
Less connected data More connected data
No graph visualization. Results
available in only tabular form.
Graph visualization as well as
tabular representation.
Queries don’t model real life so
well.
Queries modelled around real life.
SQL is slower for very large
connected datasets
Cypher Query Language is faster
for very large connected datasets.
Relational Vs Graph Databases

10. Comparison of Graph and Relational
Databases

12. Comparison of execution for Neo4j and RDBMS
Fig: Databases with sizes

13. Comparison of execution for Neo4j and RDBMS
Fig: Structural query results in millisec

14. Comparison of execution for Neo4j and RDBMS

15. Applications of Graph Database

16. Product recommendation

17. Shortest Path