euler
libvineyard
Our great sponsors
euler | libvineyard | |
---|---|---|
2 | 4 | |
2,873 | 403 | |
0.2% | - | |
0.0 | 9.1 | |
8 months ago | almost 3 years ago | |
C++ | C++ | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
euler
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euler VS CXXGraph - a user suggested alternative
2 projects | 17 Mar 2022
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GraphScope: A One-Stop Large-Scale Graph Computing System
https://github.com/alibaba/euler/wiki
libvineyard
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GraphScope: A One-Stop Large-Scale Graph Computing System
https://nbviewer.jupyter.org/github/alibaba/GraphScope/blob/...
The graphs on GraphScope is backed by vineyard (https://github.com/alibaba/libvineyard). And that enables GraphScope to have multiple specifically optimized runtimes (written in C++, rust and Python) for different tasks shares the distributed graph data in memory efficiently.
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Vineyard: An open-source in-memory data manager
6. Kubernetes-integration for large-scale big data applications
Github: https://github.com/alibaba/libvineyard (s are welcomed!)
What are some alternatives?
GraphScope - 🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统
awesome-graph-classification - A collection of important graph embedding, classification and representation learning papers with implementations.
libgrape-lite - 🍇 A C++ library for parallel graph processing (GRAPE) 🍇
pytorch_geometric_temporal - PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
feather - Feather: fast, interoperable binary data frame storage for Python, R, and more powered by Apache Arrow
efficient-gnns - Code and resources on scalable and efficient Graph Neural Networks
vg - tools for working with genome variation graphs
GNNs-Recipe - 🟠 A study guide to learn about Graph Neural Networks (GNNs)
simulacrum - A framework for procedural content generation with C++20
motion_planning - Robot path planning, mapping and exploration algorithms