parallel-disk-usage VS GraphScope

Compare parallel-disk-usage vs GraphScope and see what are their differences.

parallel-disk-usage

Highly parallelized, blazing fast directory tree analyzer (by KSXGitHub)

GraphScope

🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统 (by alibaba)
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parallel-disk-usage GraphScope
8 10
615 3,477
3.7% 0.3%
9.2 9.1
20 days ago 19 days ago
Rust C++
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

parallel-disk-usage

Posts with mentions or reviews of parallel-disk-usage. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-07-10.

GraphScope

Posts with mentions or reviews of GraphScope. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-15.
  • Show HN: Graphlearn-for-PyTorch, distributed graph learning on PyTorch
    2 projects | news.ycombinator.com | 15 May 2023
    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?

    [1]: https://github.com/alibaba/GraphScope

  • GitHub “allows” unauthorized users “merging” PRs, bypass write permission check
    2 projects | /r/github | 25 Aug 2022
  • GraphScope VS CXXGraph - a user suggested alternative
    2 projects | 17 Mar 2022
  • GraphScope on Colab: Large-Scale Graph Computing from Notebooks to Kubernetes
    1 project | news.ycombinator.com | 6 Dec 2021
    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
    1 project | news.ycombinator.com | 11 Aug 2021
  • GraphScope: A One-Stop Large-Scale Graph Computing System
    8 projects | news.ycombinator.com | 2 Feb 2021
    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...

    2 projects | news.ycombinator.com | 2 Feb 2021
    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?

When comparing parallel-disk-usage and GraphScope you can also consider the following projects:

zenith - Zenith - sort of like top or htop but with zoom-able charts, CPU, GPU, network, and disk usage

indradb - A graph database written in rust

sauce - A tool to help manage context/project specific shell-things like environment variables.

janusgraph - JanusGraph: an open-source, distributed graph database

grex - A command-line tool and Rust library with Python bindings for generating regular expressions from user-provided test cases

euler - A distributed graph deep learning framework.

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InfluxDB – Built for High-Performance Time Series Workloads
InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.
www.influxdata.com
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