Neo4j uses property graphs to extract added value of data of any company with great performance, in an agile, flexible and scalable way. 1. Performance: Graph databases such as Neo4j perform better than relational (SQL) and non-relational (NoSQL) databases. It is the world’s leading open source graph database which is developed using Java technology and it is highly scalable and NoSQL.
Graph databases are used to store and navigate relationships.Graph databases use nodes to store data entities, and edges to store relationships between entities.MongoDB also Graph Database. MongoDB offers graphing capabilities with its $graphLookup stage.
Neo4j recently released the BI Connector, which is a general JDBC driver that can process SQL queries against a Neo4j graph and return meaningful results. This enables users of tools like Tableau, that generate SQL queries, which plug directly into graph.
1.Introduction to Graph Databases
- Introduction to Graph Databases and Property Graph Model
- Comparative study between Graph Databases and RDBMS
- Comparative study between Graph Databases and NoSQL
3.Introduction to Cypher
- Basic Syntax
- Query Optimisation
- Journey from SQL to Cypher
4.Dealing with Data
- Graph Data Modelling
- Import/Export Data
- Graph Visualization
5. Drivers and Tools
- Language Drivers
- Graph Visualization Tools
- Database Schema Management System
- Database Migration Tools