1. 1. Project Mentor: Mrs. Manisha Gahirwal Project Members: Rahul Anwani(03) Akshaykumar Oswal(19) Srinivas Ravi(48) Social Networking Analysis using Graph Database
2. 2. Social Network is a highly connected data
3. 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. 4. Properties of Graph Databases 1. The underlying storage 2. The processing engine
5. 5. Why Neo4j? reliable durable and fast massively scalable highly-available expressive fast simple
6. 6. Cypher Query Language declarative graph query language what to retrieve Expressions Identifiers Operators Pattern Labels Building blocks of CQL
7. 7. Structure MATCH RETURN WHERE LIMIT ORDER BY CREATE REMOVE DELETE
8. 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. 9. Comparison of Graph and Relational Databases
10. 10. Comparison of execution for Neo4j and RDBMS Fig: Databases with sizes
11. 11. Comparison of execution for Neo4j and RDBMS Fig: Structural query results in millisec
12. 12. Comparison of execution for Neo4j and RDBMS
13. 13. Applications of Graph Database
14. 14. Product recommendation
15. 15. Shortest Path