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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