A graph database stores data as nodes and edges where nodes represent entities and edges represent relationships between those entities. Some popular graph databases include Neo4j, OrientDB, and ArangoDB. A graph has three main components: nodes which represent objects or instances, relationships which establish connections between nodes, and properties which are data attached to nodes. Graph databases are useful for applications such as fraud detection, digital asset management, network management, context-aware services, and real-time recommendations. They allow for complex queries of interconnected data.

1. NADAR SARASWATHI COLLEGE OF ARTS AND
SCIENCE,THENI.
DEPARTMENT OF COMPUTER
SCIENCE
ELEMENT OF GRAPH AND OPERATION OF GRAPH
BY:
B.POORANI
I-MSC(CS)

2. What is graph ?
 A graph database is a type of NoSQL database that is designed to handle data
with complex relationships and interconnections. In a graph database, data is
stored as nodes and edges, where nodes represent entities and edges represent the
relationships between those entities.
Some popular graph databases include Neo4j, OrientDB, and ArangoDB. These
databases provide a range of features, including support for different data models,
scalability, and high availability, and can be used for a wide variety of
applications

3. Component of graph:
Nodes: represent the objects or instances. They are equivalent to a row in
database. The node basically acts as a vertex in a graph. The nodes are grouped
by applying a label to each member.
Relationships: They are basically the edges in the graph. They have a specific
direction, type and form patterns of the data. They basically establish relationship
between nodes.
Properties: They are the information associated with the nodes.

4. Examples of Graph Data Models :
JanusGraph: These are very helpful in big data analytics. It is a scalable graph database system
open source too. JanusGraph has different features like:
◦ Storage: Many options are available for storing graph data like Cassandra.
◦ Support for transactions: There are many supports available like ACID (Atomicity, Consistency,
Isolation, and Durability) which can hold thousands of concurrent users.
◦ Searching options: Complex searching options are available and optional support too.
Neo4j: It stands for Network Exploration and Optimization 4 Java. As the name suggests this
graph database is written in Java with native graph storage and processing. Neo4j has different
features like:
◦ Scalable: Scalable through data partitioning into pieces known as shards.
◦ Higher Availability: Availability is very much high due to continuous backups and rolling upgrades.
◦ Query Language: Uses programmer-friendly query language Cypher graph query language.DGraph
main features are:

5. Applications of Graph Data Model:
• Graph data models are very much used in fraud detection which itself is very much useful and
important.
• It is used in Digital asset management which provides a scalable database model to keep track
of digital assets.
• It is used in Network management which alerts a network administrator about problems in a
network.
• It is used in Context-aware services by giving traffic updates and many more.
• It is used in Real-Time Recommendation Engines which provide a better user experience.

6. Thank you