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Abstract Graphs are increasingly used in research, industry, and government. This has led to a wide range of analytical and graph-processing tools. There are various tools and platforms for graph processing. Many network based platforms, tools and storage systems have been presented over time. Each system evaluates its effectiveness and usability in processing graph data using different statistics and criteria. As a result, comparing the various systems' performances becomes challenging. This study benchamark popular network analysis tools— NetworkX, RustworkX, Igraph, EasyGraph, and Graph-tool— by evaluating their performance and extracted community engagement metrics, such as the number of downloads, stars, and forks. We benchmark the library's performance on three open-source datasets, one custom dataset, and twelve network analysis methods. The findings reveal that while NetworkX is highly popular, it exhibits slower performance in most benchmarks compared to Graph-tool and Igraph, which are faster and more efficient despite their lower popularity. The continued popularity of NetworkX may be attributed to factors like well-documented methods and a user-friendly API, though this warrants further investigation. This research provides valuable insights for practitioners, researchers, and developers, helping them make informed decisions when selecting network analysis tools. The study emphasizes the trade-off between user-friendliness and performance, suggesting that the optimal tool choice depends on project-specific requirements.
Amure et al. (2024) studied this question.