Tigergraph

---
name: tigergraph
description: "Distributed graph analytics platform with GSQL query language. Use when running fraud detection on transaction networks, analyzing supply chain dependencies, building customer 360 views, computing PageRank on billion-edge graphs, or querying deep multi-hop relationships in real time."
version: "1.0.0"
author: BytesAgain
homepage: https://bytesagain.com
source: https://github.com/bytesagain/ai-skills
tags: [tigergraph, graph-database, gsql, analytics, fraud-detection, supply-chain]
---

# TigerGraph Reference

Distributed graph analytics platform for real-time deep-link analysis on massive datasets. TigerGraph uses GSQL, a SQL-like graph query language designed for parallel traversal across 100+ billion edges with sub-second response times.

## When to Use

- Fraud detection: identify suspicious transaction rings and money laundering patterns
- Supply chain: trace multi-hop dependencies and find bottleneck nodes
- Customer 360: merge entity data across multiple sources into a unified graph
- Recommendation engines: collaborative filtering at scale using graph traversal
- Network analytics: map telecom or IT infrastructure relationships
- Knowledge graphs: build and query enterprise knowledge bases

## Commands

| Command | Description |
|---------|-------------|
| `intro` | Architecture overview, TigerGraph vs Neo4j comparison, use cases, installation |
| `gsql` | GSQL schema definition, data loading jobs, queries (ad-hoc and installed), PageRank implementation |
| `api` | REST API endpoints for vertices/edges/queries, pyTigerGraph Python SDK, GraphStudio visual IDE |

## Requirements

- No external dependencies — outputs reference documentation only
- No API keys required
- No network access needed

## Feedback

https://bytesagain.com/feedback/