Graph Visualization Development for Apps and SaaS Products

The hierarchical layout arranges nodes hierarchically and keeps edges in the same overall orientation (top-to-bottom, left-to-right, or in other directions). It reduces the number of link crossings and prevents overlaps, ensuring readability of the graph. 

The graph visually represents the data organization and relationships. Each parent node can lead to many other nodes and vice versa. You can select a layout to change the composition of nodes and boost readability. 

Here’s a visual presentation of data categorized into datasets and presented visually in swimlanes. Each node comes with a collapsable property section that provides a glimpse into datasets’ subcategories and details. 

This graph type uses clearly separated nodes and edges to add clarity to the connections between individual nodes. Data is placed around the circle and edges represent relationships between points. You can use different colors to group nodes and change edge thickness to depict data accumulation. 

Disk layout allows users to categorize large datasets into several groups. It helps keep the workspace clear and simplifies searching for categories of particular nodes. Nodes can be stored in order within each of them.

The arc graph connects nodes placed along a single line, highlighting clusters and bridges. Wider links demonstrate stronger connections between nodes. Thanks to its structure, users can add and display labels for each node while keeping full readability. 

This indefinitely expanded visualization is built with GoJS and uses GraphQL to download data from the server. To improve performance, It uses virtualization activated with several thousand nodes, as there is no need to render objects not currently visible on the screen.