StellarGraph

Machine Learning on Graphs for network-structured data.

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

What is StellarGraph?

StellarGraph is a Python library that enables machine learning on graph-structured data, providing tools and algorithms to analyze complex networks and relationships within the data.

Key differentiator

StellarGraph stands out by providing comprehensive support for graph neural networks and deep learning on graphs, making it ideal for complex network analysis tasks.

Capability profile

Strength Radar

Graph neural net…Supports various…Integration with…

Honest assessment

Strengths & Weaknesses

↑ Strengths

Graph neural networks for node classification and link prediction

Supports various graph types including homogeneous, heterogeneous, and dynamic graphs

Integration with TensorFlow and Keras for deep learning on graphs

Fit analysis

Who is it for?

✓ Best for

Researchers and practitioners working with graph-structured data who need advanced machine learning capabilities.

Projects requiring integration of TensorFlow or Keras for deep learning on graphs.

✕ Not a fit for

Developers looking for a cloud-based service without the need to manage local installations.

Teams that require real-time processing and cannot afford the latency associated with local computation.

Cost structure

Pricing

Free Tier

None

Starts at

See website

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Ecosystem

Relationships

Next step

Get Started with StellarGraph

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →