Counter vs Netron
| Tagline | Minimalist self-hosted hit counter and page-view tracker | Interactive visualizer for neural network and machine learning model graphs |
| Category | Product & Web Analytics | Product & Web Analytics |
| Replaces | Google Analytics, Hotjar | Google Analytics, Mixpanel, Amplitude |
| GitHub stars | 2k | 33k |
| Language | Go | Python |
| License | MIT | MIT |
| Self-host difficulty | 1/5 Effortless | 1/5 Effortless |
| Deploy options | One-Click Docker Manual | Manual |
| Managed hosting | ||
| Last updated | 1 month ago | 8 days ago |
| View repo | View repo |
Where each falls short
The honest trade-offs — what you give up with each, versus the proprietary tools they replace.
Counter
- No funnel, cohort, or retention analysis whatsoever
- No custom event tracking beyond page hits
- Data aggregation is coarse; no drill-down by browser, OS, or campaign
Netron
- Purely a model visualization tool; no runtime analytics, dashboards, or event tracking
- Does not replace web or product analytics SaaS in any meaningful way
- No team collaboration or sharing features beyond exporting images
- No support for real-time or streaming model inference monitoring
Bottom line
Both are a similar lift to self-host; choose Netron for the larger community and ecosystem. Netron has seen more recent development. Open each guide below for deploy steps and the full feature gap.
Netron
Interactive visualizer for neural network and machine learning model graphs