A distributed native parallel graph database and analytics platform designed for enterprises to perform deep link analysis on massive datasets in real-time, uncovering critical insights from complex connected data.
TigerGraph is a high-performance graph analytics platform built for handling large-scale, complex, and interconnected data. It serves data scientists, architects, and developers in enterprises across finance, supply chain, and cybersecurity who need to understand relationships within their data. The platform's unique value proposition stems from its native parallel graph architecture, which allows it to execute deep link queries (3 to 10+ hops) in real-time. This capability enables advanced use cases like fraud detection, customer 360, supply chain optimization, and personalized recommendations at a scale that traditional databases struggle with. By using its own powerful, SQL-like language called GSQL, TigerGraph provides the speed and scalability necessary for modern machine learning and AI applications built on graph data.
Enterprise data scientists, data architects, developers, and business analysts working in sectors like financial services, e-commerce, healthcare, and manufacturing on complex, large-scale data problems.
Based on 0 reviews
2012
Redwood City, USA
Cloud Free
An always-free tier for learning and small projects. Includes one graph solution with up to 50GB of storage on shared infrastructure.
Free
Cloud Pay-As-You-Go
For production applications with pricing based on vCPU hours, storage, backup, and data transfer. Offers various instance sizes and dedicated compute.
Usage-based
Enterprise Edition
A self-managed solution for deployment in a private cloud or on-premise data center. Includes enterprise-grade security, high availability, and dedicated support.
Custom
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