- NetworkX (http://networkx.github.io): easy to install & use. slow but ok for many occasions.
- NetworKit: seems to be easier to install & pretty fast.
- graph-tool: it uses the Boost library and very fast. A bit difficult to satisfy all the installation requirements. Fairly ok to install with Anaconda (Python)
- igraph (http://igraph.org)
- Stanford Network Analysis Platform (http://snap.stanford.edu/index.html)
- GraphLab, GraphChi
- GraphX: a graph library on top of (Apache Spark).
Probably not so useful #
- APGL (another Python graph library)
- http://github.com/xslogic/phoebus - "Phoebus is a distributed framework for large scale graph processing written in Erlang."
Incoming Links #
Related Articles (Article 0) #
Suggested Pages #
- 0.184 Link analysis
- 0.102 Simplicial complex
- 0.062 Dynamical system
- 0.042 Complex systems
- 0.028 Diffusion of innovations
- 0.025 Mark Newman
- 0.025 Python/Visualization
- 0.025 Cosma Shalizi
- 0.025 [[https://github.com/twitter/cassovary]]
- 0.025 Biological network
- More suggestions...