Storage & Computing
Most knowledge graph storage engine are not designed to compute in real-time. This makes graph analytics embarrassingly slow.
Visualization & Performance
Graphical visualization is a must-have with any knowledge graph, but in the era of Enterprise 2.0, most KG visualization are not performance tuned, therefore incapable of handling large amount of data.
Graph is high-dimensional, it’s utterly important and crucial to leverage visualization to not only make your whole operational process painless and visually appealing but also to make the results self-explaining and intuitive.
Knowledge Graph is a living thing, there are multiple ways to interact with it, one of the most powerful ways is to program against it, i.e., using the powerful yet super-easy uQL to dynamically extract subgraphs out of a much larger KG, the whole process is pain free.
Super-Deep Graph Computing
Unlike today’s most knowledge graph solutions which do NOT have the capacity to compute in real-time and to search deeply within the graph – Ultipa is capable of super-deep graph computing, many hops deeper, it has the capacity to traverse over 1 Billion nodes and edges per second per instance.
The core competency of Ultipa's storage and computing engine is speed!
Ultipa's native graph data modeling is naturally compliant with KGs , and our toolkits are friendly to use even for newbies.
Interpretability is essential for potentially sophisticated knowledge graph operations, with Ultipa's native graph computing and high visualization,we white-box AI and KG.