Why it matters

Connections and relationships between data points are critical to modern applications. Whether modeling social networks, fraud detection, recommendation engines, or supply chains, graph technology provides the most natural and powerful way to represent and traverse these relationships. Without native graph support, organizations risk missing insights hidden in the links between their data.

How FlexVertex solves it

FlexVertex was designed from day one with graph use cases at its core. We provide full, native support for properties on both vertices and edges, ensuring expressive, real-world modeling. But we go further: graph is deeply integrated into the FlexVertex Data Multiverse™, so relationships are not limited to graph alone. Graph data can embed or link to other models such as vector-native embeddings, documents, key/value, tabular, and time series. This multi-model integration means you can start a query from a graph, a document, or even an embedding, and navigate seamlessly across data types.

What you get

Full graph model – native properties on vertices, edges, and connections for expressive design

Multi-model traversal – move fluidly between embeddings, graph, documents, key/value, tabular, and time series

Context-rich queries – expand searches from one model into all related models with ease

Future flexibility – architects and developers can mix models without rigid silos