CyrilFeng/karma
新数据洞察方式 observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 28
- Release rhythm 35
- Longevity 34
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 482
- days_rel: n/a
- days_push: 434
- n_releases_24m: 0
Adoption not part of the score
1008 stars · 87 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Karma is a self-hosted data insight tool described as an 'executable mind map', built on Trino, that lets users configure SQL-based data sources and visually compose analysis flows as node graphs. It aims to give business teams direct control over data exploration and experiment analysis without heavy dashboard development.
Use cases
- analyze whether a marketing campaign improved lead conversion
- measure impact of sms or push notifications on user exposure and behavior
- compare user metrics before and after an activity or event
- build self-service data analysis flows without writing dashboards
- connect multiple SQL data sources via a shared user id
- explore business questions like GMV or retention changes around an experiment
When to choose
- you need a polished traditional BI dashboard with charts and reports
- your data is not queryable via Trino SQL
- you require a permissively licensed project for commercial use (no license file is present)
Facets
application · maturity active
data-visualization analytics etl web-framework data-science analytics data-visualization self-hosted self-hosted jvm mind-map trino data-analysis business-intelligence sql self-service-analytics experiment-analysis web-server docker
1 source
- readme: https://github.com/CyrilFeng/karma · fetched 2026-08-28 · 27cbeeaa8a65
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| CyrilFeng/karma | main | 32 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem