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🕸️ GraphDB

GraphDB is an interactive graph database application designed to simplify the exploration, querying, and visualization of connected data. Built using Neo4j and Streamlit, the application enables users to manage graph data, execute Cypher queries, visualize relationships, and interact with the database through an intuitive interface.

The project bridges the gap between traditional database management and graph analytics by allowing users to explore complex relationships without requiring extensive knowledge of graph query languages. It demonstrates practical applications of graph databases in domains such as social networks, recommendation systems, knowledge graphs, and relationship analysis.


✨ Features

  • 📊 Interactive graph visualization
  • 🔍 Natural language query support
  • 🕸️ Neo4j graph database integration
  • 📝 Cypher query execution
  • ➕ Create, update, and delete nodes & relationships
  • 📈 Interactive graph analytics
  • 🎯 Relationship exploration
  • 💻 User-friendly Streamlit interface

🛠️ Tech Stack

  • Language: Python
  • Database: Neo4j
  • Framework: Streamlit
  • Query Language: Cypher
  • Visualization: Neo4j Graph Visualization
  • Libraries: Neo4j Python Driver, Pandas

🚀 Core Functionalities

🔍 Graph Querying

Execute Cypher queries to retrieve connected data and explore relationships between entities.

🕸️ Relationship Visualization

Display nodes and relationships through an interactive graph interface for intuitive exploration.

✍️ Natural Language Search

Convert user-friendly questions into graph queries, making database interaction more accessible.

📊 Graph Analytics

Analyze connected datasets to discover hidden relationships and insights.

⚙️ Database Management

Create, modify, and delete nodes and relationships directly from the application.


🎯 Applications

  • Knowledge Graphs
  • Social Network Analysis
  • Recommendation Systems
  • Fraud Detection
  • Network Analysis
  • Relationship Discovery

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Interactive graph database explorer with natural language querying, Neo4j visualization, and AI-assisted graph analytics.

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