![]() ![]() Keylines and its React sister library Regraph is a commercial product by cambridge intelligence with a powerful visualisation engine that supports canvas and WebGL rendering. There are other wrapper libraries like react-vis-force and react-d3-graph but the former is no longer maintained and the later still has a lot of room to cover to catch up with the other libraries. Here’s a sample example of using D3 to visualise the Les Mis graph. It contains other helper libraries such as D3-force, but most of the other primitives have to be implemented by the user. However, the amount of time needed to build up a graph visualisation solution to match the capabilities of keylines or G6 is massive. ![]() D3ĭ3 is a full-blown data visualisation framework and one of the most popular choices to make interactive bar charts, line charts, geospatial plots and yes, network plots. In this section, we go into the individual products in detail and our general experience with them (when applicable). This could include a time bar filter or a minimap to help a user navigate through the canvas. Out of the box components that would speed up product development. All these additional functionalities would significantly cut down on the development time required. ![]() This could include layout options, pathfinding algorithms or even network detection algorithms. This refers to the set of available APIs to allow a user to perform a graph operation. While WebGL is more performant as it leverages the GPU processing power of a machine, it is also harder to work with, which means there tends to be a tradeoff between performance, ease of use and capabilities. Canvas performance reaches the limit at 5k nodes and 5k edges while WebGL is usable until 10k nodes and 11k edges. Using a 2015 macbook, SVG performance tops gives workable performance until it reaches 2k nodes and 2k edges. Yworks, a diagrammatic library SDK provider, has a nice comparison of the 3 rendering methods. The factor that has the greatest impact on performance is the rendering engine which the underlying framework uses. We identified 3 areas where we are interested in comparing across the different products: performance / rendering engine, algorithms available and out of the box components. Here’s the list of 8 libraries we shortlisted for our evaluation: While performance might be poorer than native operating systems capabilities, they are more than good enough for most data visualisation needs. These libraries could easily be integrated into a larger web application or even published as a desktop electron application. Javascript with its universal browser support is an extremely attractive solution to build an interactive web application. These software libraries are good for an individual analyst but are hard to integrate into larger product offerings. There are many other graph visualisation libraries available including popular desktop applications like Gephi or Cytoscape, and libraries coupled with programming languages like visualisation packages within igraph and networkx. Here, we are looking to evaluate libraries for data exploration and investigation. While graph visualisation libraries are often used for diagrammatic drawings such as UML diagrams or mind maps, those areas are out of our focus. We hope this will be a useful guide for product owners or developers looking to integrate graph visualisation into their application. ![]() This covers both open source and paid libraries. In this article, we document our findings on the state of Javascript graph visualisation libraries. The growth in the graph database ecosystem has also resulted in a better understanding of the benefits of a graph data representation.Īs part of the development of Motif, our graph intelligence software, we evaluated a range of network visualisation solutions to see which tool best fits our use case. There have been emerging use cases to use graphs to understand IOT, social network or transaction data. Graph / Network visualisation is a subcategory within the data visualisation space that has grown in popularity over the past few years. ![]()
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