TigerGraph

The platform provides a graph‑based storage engine that captures entities and their relationships, enabling queries that traverse many hops in milliseconds. It supports petabyte‑scale datasets and parallel computation, allowing real‑time analytics on large, complex networks without the performance degradation typical of relational joins.

Developers and data engineers use it to build applications such as fraud detection, anti‑money‑laundering, entity resolution, recommendation engines, customer 360 views, and supply‑chain monitoring. The system exposes a query language and APIs that let users model connected data, execute deep traversals, and integrate AI‑driven analytics that leverage the underlying graph structure.

What distinguishes the product is its focus on enterprise‑grade performance and AI readiness: it claims sub‑100 ms response times for queries over billions of relationships, unlimited parallel storage, and built‑in capabilities to uncover hidden connections that traditional databases cannot reveal.