Graph

Graph data structure natively represents relationships between data. The two main parts of a graph are:

• Vertices (or nodes) that represent objects and their properties

• Edges (or connections) that represent links between two vertices

Some of the key benefits are:

• Enhanced Data Relationships & Insights

  • Unlike traditional tabular data analysis, graph analytics enables users to explore intricate relationships between data points, providing a holistic view of connections and dependencies.

• Identify unusual connections

  • Graph analytics is particularly effective in identifying fraudulent activities by detecting unusual patterns, anomalies, and suspicious connections in financial transactions, cybersecurity, and compliance monitoring.

• Faster query processing

  • Graph analytics fundamentally changes the way relationships are queried and analyzed. By eliminating the need for expensive join operations and enabling high-speed relationship traversal, graph databases significantly outperform relational databases for complex, connected data.

Overview

• Visual Graph
  • Requirements
  • Editor webapp
  • Explorer webapp
  • Recipes
  • Graph Search Agent Tool
• Neo4j

The following table lists available plugins that you can use to work on graph data structures.

Plugin	Description	Support tier
Visual Graph plugin	A set of Webapps, recipes and Agent Tool to collaboratively build & leverage graphs.	Tier 2 support
Graph analytics plugin	Analyze and visualize graph data using in-memory tools.	Not supported
Neo4j plugin	Read and write from/to the Neo4j graph database.	Not supported