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Welcome to TigerGraphX

TigerGraphX is a high-level Python library offering a unified, Python-native interface for graph databases, advanced analytics, and GraphRAG workflows. Combining the simplicity of NetworkX with the advanced capabilities of TigerGraph, including tgCloud, it empowers Python developers to harness the power of graphs without the need to learn query languages like Cypher or GSQL.

TigerGraphX is designed for two main audiences, catering to different use cases while maintaining an easy-to-use, developer-friendly experience:

Who Should Use TigerGraphX?

1. Python Developers for Graph Analytics with TigerGraph

If you’re a Python developer interested in performing graph analytics with TigerGraph, TigerGraphX provides:

  • Python-Native APIs: No need to learn complex query languages like GSQL or Cypher.
  • Seamless Integration: Easily perform CRUD operations, multi-hop queries, and advanced analytics directly from Python.
  • Scalability: Leverage the powerful performance of TigerGraph for large-scale graph processing.

Start here:

  • Introduction to TigerGraphX: Discover the features and benefits of using TigerGraphX for graph database management and analytics.
  • Getting Started: Learn how to install and set up TigerGraphX.
  • Quick Start Guide: Quickly set up TigerGraphX and build your first graph with this step-by-step guide.

2. Python Developers for GraphRAG Workflows

If you’re a Python developer building GraphRAG applications, TigerGraphX enables you to:

  • Use TigerGraph as a scalable database for storing and retrieving graph and vector data generated by GraphRAG algorithms.
  • Build token-aware LLM workflows for advanced AI applications.
  • Utilize context builders to streamline data preparation for large language models.

Start here:

Start unlocking the power of graphs with TigerGraphX today!