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/