Network science

• 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."
• Conedy
• Cassovary

Incoming Links #

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