alibaba/euler

Health v2 · maintenance only

Adoption not part of the score

2897 stars · 554 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Euler is a distributed graph deep learning framework developed by Alibaba for running graph neural network algorithms on large-scale graphs. It provides a graph query language, attribute indexing, message passing interfaces, and model examples for attributed, heterogeneous, and knowledge graphs.

Use cases

• train graph neural networks on billion-edge graphs
• compute node embeddings with node2vec or random walks
• run GraphSAGE or GCN models distributed across a cluster
• apply deep learning to knowledge graphs
• classify nodes and graphs with attributed graph data

When to choose

• you need distributed training of GNNs on very large graphs
• you work with heterogeneous or knowledge graphs in a C++/TensorFlow stack
• you want a battle-tested industrial graph learning framework from Alibaba

When to avoid

• you want a modern actively developed GNN library like PyTorch Geometric or DGL
• your graphs are small enough for single-machine libraries
• you need Windows or macOS support

Facets

framework · maturity maintenance

machine-learning deep-learning search-engine machine-learning deep-learning graph-processing cpp python graph-neural-networks graph-embedding distributed-training network-embedding gcn graphsage node2vec knowledge-graph algorithms linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="alibaba/euler")