OSI-licensed only · self-hostable
Gephi is itself open source: its README says the main source code is dual-licensed under CDDL 1.0 and GPLv3, and the repository shows GPL-3.0. It is described as an open-source platform for visualising and manipulating large graphs, built on the NetBeans Platform. People look for alternatives when they want a web component, a scripting library or a different desktop workflow.
Every tool below is under an OSI-approved licence, checked against its repository. They fall into desktop applications, JavaScript libraries for the web, and Python or C analysis libraries.
Licences checked against each repository on November 7, 2026.
| Tool | Best for | Licence | Runs as |
|---|---|---|---|
| Cytoscape | Biological and general network analysis on the desktop | LGPL-2.1 | Desktop app |
| Cytoscape.js | Interactive graphs in web apps | MIT | Server |
| Graphia | Visual analytics of large datasets | GPL-3.0 | Desktop app |
| Tulip | Very large graphs | LGPL-3.0 | Desktop app |
| Sigma.js | Large graphs in the browser | MIT | Server |
| NetworkX | Network analysis in Python | BSD-3-Clause | Desktop app |
| igraph | Efficient network analysis in C | GPL-2.0 | Desktop app |
| cosmos.gl | GPU-accelerated force graphs in the browser | MIT | Server |
Best for: Biological and general network analysis on the desktop
An open-source platform for network analysis and visualisation. The cytoscape-impl repository holds the actual implementations of Cytoscape 3 applications, desktop and headless.
Best for: Interactive graphs in web apps
A graph theory (network) library for visualisation and analysis, with a graph model and an optional renderer for interactive graphs.
Best for: Visual analytics of large datasets
A powerful open-source visual analytics application for analysing large, complex datasets.
Best for: Very large graphs
An open-source, cross-platform framework for analysing, drawing and visualising very large graphs, with support for millions of nodes and edges.
Best for: Large graphs in the browser
An open-source JavaScript library for visualising graphs of thousands of nodes and edges, using WebGL and built on top of graphology.
Best for: Network analysis in Python
A Python package for creating, manipulating and studying complex networks.
Best for: Efficient network analysis in C
A C library for complex network analysis and graph theory, with emphasis on efficiency, portability and ease of use.
Best for: GPU-accelerated force graphs in the browser
A high-performance WebGL force-graph algorithm and rendering engine in which computation and drawing run on the GPU.
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| If you need… | Start with |
|---|---|
| A desktop app like Gephi for network analysis | Cytoscape or Graphia |
| Interactive graph in a website | Cytoscape.js or Sigma.js |
| Very large graphs rendered on the GPU | cosmos.gl or Tulip |
| Scripted analysis in Python | NetworkX |
| Fast analysis in C | igraph |
Quick answers to common questions
Yes. Its README says the main source code is dual-licensed under CDDL 1.0 and GPLv3, and you can choose either.
Cytoscape and Graphia are desktop applications for network visualisation and analysis. Tulip is a desktop framework aimed at very large graphs.
Cytoscape.js and Sigma.js are both MIT-licensed JavaScript libraries. cosmos.gl is an MIT-licensed WebGL engine for very large force graphs.
Yes. NetworkX is a Python package for studying complex networks and igraph is a C library for the same job.
Tulip's README says it no longer offers pre-compiled binaries after version 6.0.1, so you compile from source.
List it on TechLogHub and we'll review it for this page.
