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
4. Properties of Graph Databases 1. The underlying storage 2.
The processing engine
5. Why Neo4j? reliable durable and fast massively scalable
highly-available expressive fast simple
6. Cypher Query Language declarative graph query language what
to retrieve Expressions Identifiers Operators Pattern Labels
Building blocks of CQL
7. Structure MATCH RETURN WHERE LIMIT ORDER BY CREATE REMOVE
DELETE
8. 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 dont 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
9. Comparison of Graph and Relational Databases
10. Comparison of execution for Neo4j and RDBMS Fig: Databases
with sizes
11. Comparison of execution for Neo4j and RDBMS Fig: Structural
query results in millisec