Nstream
A faster way to build streaming data applications
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.
