CXXGraph
GraphScope
Our great sponsors
CXXGraph | GraphScope | |
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84 | 10 | |
392 | 3,101 | |
- | 0.8% | |
8.5 | 9.7 | |
4 days ago | 2 days ago | |
C++ | C++ | |
GNU Affero General Public License v3.0 | 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.
CXXGraph
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Hacktoberfest is ON CXXGraph
Actual Web Site
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Revolutionizing Data Processing with CXXGraph: A Comprehensive Guide to Graph Data Structures in C++
CXXGraph is a C++ library for graph data structures that provides an easy-to-use interface for creating and processing direct and nondirect graphs. CXXGraph provides a simplified interface for creating and manipulating graphs. Using CXXGraph, developers can create graphs, add and remove edges, and perform various graph processing algorithms.
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CXXGraph Library : Header-Only C++ Library for Graph Representation and Algorithms
If you have 5 minutes to get in touch, click on the project or write to me at [email protected]
- 2 Weeks of Hacktoberfest, How is it going??
- Hacktoberfest is started, give your contribution!
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Hacktobefest 2022: My Repo
View on GitHub
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GraphScope VS CXXGraph - a user suggested alternative
2 projects | 17 Mar 2022
A Fast Graph library in C++
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libgrape-lite VS CXXGraph - a user suggested alternative
2 projects | 17 Mar 2022
A good library for graph algorithms
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euler VS CXXGraph - a user suggested alternative
2 projects | 17 Mar 2022
Good alternative for algorithms
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xgboost VS CXXGraph - a user suggested alternative
2 projects | 28 Feb 2022
GraphScope
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Show HN: Graphlearn-for-PyTorch, distributed graph learning on PyTorch
Optimizing distributed sampling and feature lookup looks really attractive. It's really challenging to deploy GNN training at an industrial-scale for a large graph.
Will GLT be part of graphscope[1] and replacing the current graphscope-for-learning implementation?
- GitHub “allows” unauthorized users “merging” PRs, bypass write permission check
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GraphScope VS CXXGraph - a user suggested alternative
2 projects | 17 Mar 2022
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GraphScope on Colab: Large-Scale Graph Computing from Notebooks to Kubernetes
We are glad to announce the landing of GraphScope on Colab: https://colab.research.google.com/github/alibaba/GraphScope.
GraphScope is a one-stop graph computing systems from Alibaba aimed to address challenges in large-scale graph computation in real production environments. GraphScope releases v0.9, enabling data scientists to develop graph computing workflows for analytical, interactive query and GNN workloads on small graphs in jupyter notebooks in a interactive manner. Once finishing the development and debugging, users can easily deployed their workflows to Kubernetes with one-line change!
To try GraphScope, you could find it on Colab[1], Jupyter Hub[2], or install GraphScope to your environment using pip by:
pip3 install graphscope
For more details of our v0.9 release, please refer to https://github.com/alibaba/GraphScope/releases/tag/v0.9.0
[1]: https://colab.research.google.com/github/alibaba/GraphScope/...
- GraphScope v0.6 Released: Code with Eager, Executive with Lazy
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GraphScope: A One-Stop Large-Scale Graph Computing System
Thanks for you interests on GraphScope!
We do have a concrete plan for k8s-less deployment and we already have an issue [1] to track that. That will be available before the end of March 2021.
To simplify the environment setup process we will release a docker image for end-users, but without docker will be ok as well (requires building from sources).
GraphScope use vineyard [2] as the storage layer for im-memory graph data structures. And current the graph type (aka. ArrowPropertyFragment in GraphScope) uses a set of arrow tables and arrays under the hood.
GraphScope supports a `to_vineyard_dataframe` method on the computation context [3]. We also has a plan for integration between vineyard and dask (may could be delivered in March as well). At that time the interop between dask would be straightforward.
[1]: https://github.com/alibaba/GraphScope/discussions/113
[2]: https://github.com/alibaba/libvineyard
[3]: https://graphscope.io/docs/reference/context.html#graphscope...
GraphScope is a unified distributed graph computing platform that provides a one-stop environment for performing diverse graph operations on a cluster of computers through a user-friendly Python interface. GraphScope makes multi-staged processing of large-scale graph data on compute clusters simple by combining several important pieces of Alibaba technology for analytics, interactive, and graph neural networks (GNN) computation, respectively, and the vineyard store that offers efficient in-memory data transfers.
We just released the version 0.2.0. And along with the release, we launched a public JupyterLab service where you can have a try in your browser: https://try.graphscope.app
Github: https://github.com/alibaba/graphscope. (stars are welcome :)
What are some alternatives?
sirix - SirixDB is an an embeddable, bitemporal, append-only database system and event store, storing immutable lightweight snapshots. It keeps the full history of each resource. Every commit stores a space-efficient snapshot through structural sharing. It is log-structured and never overwrites data. SirixDB uses a novel page-level versioning approach.
janusgraph - JanusGraph: an open-source, distributed graph database
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
indradb - A graph database written in rust
graphlite - A lightweight C++ graph library
libvineyard - vineyard (v6d): an in-memory immutable data manager. [Moved to: https://github.com/alibaba/v6d]
shields - Concise, consistent, and legible badges in SVG and raster format
euler - A distributed graph deep learning framework.
bitcart - https://bitcart.ai
MPAndroidChart - A powerful 🚀 Android chart view / graph view library, supporting line- bar- pie- radar- bubble- and candlestick charts as well as scaling, panning and animations.
benchmark - A microbenchmark support library
sonic - 🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.