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A faster, more scalable graph data platform

Graph databases — where data lives in the form of vertices and edges rather than rows and columns — are ideal for repre­senting customers’ interests, behaviors, or connections. But they’re not always optimized for computing speed. TigerGraph was built from the ground up to represent graphs as compu­ta­tional models, where each vertex is associated with a different function, trans­forming them into active compute-storage elements — and supporting fast, massively parallel computation.

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