Products

至轻云

Uses AI

Big data computing platform based on Spark

zhiqingyun.isxcode.com Source★ 95Data & Analytics / Data Integration & Warehousing

AI Benchmark
Desktop
Mobile
Monthly visits
None yet
No traffic data yet
Public revenue
Undisclosed
No public revenue evidence yet
Entry price
Free
No monthly subscription pricing
Launched
2y ago
2024-07-09 · Est.

Traffic

Monthly visits

No traffic data yet.

Marketing moves

Launches, search & content, referrals, promotions
  • Launched on V2EXLaunch

    [至轻云] 超轻量级大数据计算平台,持续更新 — Github: Docker 一键部署,快来尝试 docker run -p 8080:8080 isxcode/zhiqingyun 👉 手把手安装教学 演示地址: 体验账号:user001 账号密码:welcome1 新功能:作业结果传递

    Nov 12, 2024 · 2y agoLaunch page

  • Launched on V2EX (9 comments)Launch

    轻量级大数据计算平台 — 产品: 至轻云 官网: github: 产品体验: 账号: user001 密码: welcome1 欢迎大家提出宝贵的建议

    Aug 27, 2024 · 2y agoLaunch page

  • Launched on Product HuntLaunch

    Big data computing platform based on Spark

    Jul 9, 2024 · 2y agoLaunch page

Open Source & Self-Hosting

GitHub · MCP / Skill
Last commit 2026-08-01
GitHub Stars
★ 95
Forks
21
License
See repository
Primary language
—

Traffic sources

Traffic breakdown

No traffic channel or country breakdown data for this website yet.

Search

Domain authority —Domain registered 2018-11-05

No search keyword data for this website yet.

Traffic data: Vaneform

Pricing

Pricing page not identified yet, or no public pricing listed.

Pages & changes

Tracked since 2024-07-09

Key pages

Weekly snapshots

Changes

No pricing, plan, or positioning changes detected since tracking started.

Questions & evidence

What is 至轻云 and what platforms does it support?
至轻云 is catalogued under Data Integration & Warehousing: Big data computing platform based on Spark. Supported platforms: Web.
Is 至轻云 open source?
至轻云 has a public repository (https://github.com/isxcode/spark-yun) with its source repository published, recording 95 GitHub stars.Source

Related products in this category

Data & Analytics / Data Integration & Warehousing

These products share a catalog category. Compare customer tasks, features and deployment requirements before treating them as alternatives.