--- title: "athina-evals vs netdata" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/athina-ai-athina-evals-vs-netdata-netdata" tools: ["athina-ai-athina-evals", "netdata-netdata"] --- # athina-evals vs netdata *GraphCanon updated Jul 11, 2026* ## Verdict Pick athina-evals when athina-evals is primarily Python; netdata is Go; pick netdata when netdata is primarily Go; athina-evals is Python. [athina-evals](https://docs.athina.ai) reports 301 GitHub stars, 22 forks, and 3 open issues, last pushed Jun 6, 2025. [netdata](https://www.netdata.cloud) has 80k stars, 6.5k forks, and 359 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [athina-evals's repository](https://github.com/athina-ai/athina-evals) and [netdata's repository](https://github.com/netdata/netdata). | | [athina-evals](/tools/athina-ai-athina-evals.md) | [netdata](/tools/netdata-netdata.md) | | --- | --- | --- | | Tagline | Python SDK for running evaluations on LLM generated responses | The fastest path to AI-powered full stack observability, even for lean teams. | | Stars | 301 | 79,594 | | Forks | 22 | 6,515 | | Open issues | 3 | 359 | | Language | Python | Go | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | - | GPL-3.0 | | Categories | Developer Tools, Evaluation & Observability, LLM Frameworks | Developer Tools, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [athina-evals](/tools/athina-ai-athina-evals.md) | [netdata](/tools/netdata-netdata.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 399d | 0d | | Open issues (now) | 3 | 359 | | Security scan | No lockfile | No MCP manifest | | Full report | [trust report](/tools/athina-ai-athina-evals/trust.md) | [trust report](/tools/netdata-netdata/trust.md) | ## Choose when ### Choose athina-evals if… - athina-evals is primarily Python; netdata is Go. - Tags unique to athina-evals: evaluation, evaluation-framework, evaluation-metrics, llm-eval. - Also covers LLM Frameworks. ### Choose netdata if… - netdata is primarily Go; athina-evals is Python. - Tags unique to netdata: ai, alerting, cncf, data-visualization. - More GitHub stars (80k vs 301) - visibility, not fit. ## When NOT to use athina-evals - Last GitHub push was 400 days ago (dormant maintenance, Jun 6, 2025). Validate activity before betting a new project on athina-evals. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use netdata - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ## Common questions ### What is the difference between athina-evals and netdata? athina-evals: Python SDK for running evaluations on LLM generated responses. netdata: The fastest path to AI-powered full stack observability, even for lean teams.. See the comparison table for live GitHub stats and shared categories. ### When should I choose athina-evals over netdata? Choose athina-evals over netdata when athina-evals is primarily Python; netdata is Go; Tags unique to athina-evals: evaluation, evaluation-framework, evaluation-metrics, llm-eval; Also covers LLM Frameworks. ### When should I choose netdata over athina-evals? Choose netdata over athina-evals when netdata is primarily Go; athina-evals is Python; Tags unique to netdata: ai, alerting, cncf, data-visualization; More GitHub stars (80k vs 301) - visibility, not fit. ### When should I avoid athina-evals? Last GitHub push was 400 days ago (dormant maintenance, Jun 6, 2025). Validate activity before betting a new project on athina-evals. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid netdata? Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ### Is athina-evals or netdata more popular on GitHub? netdata has more GitHub stars (79,594 vs 301). Stars measure visibility, not whether either tool fits your constraints. ### Are athina-evals and netdata open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to athina-evals or netdata? GraphCanon lists graph-backed alternatives at [athina-evals alternatives](/tools/athina-ai-athina-evals/alternatives) and [netdata alternatives](/tools/netdata-netdata/alternatives) ([athina-evals markdown twin](/tools/athina-ai-athina-evals/alternatives.md), [netdata markdown twin](/tools/netdata-netdata/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/athina-ai-athina-evals-vs-netdata-netdata.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, athina-evals or netdata? athina-evals: Dormant. netdata: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for athina-evals and netdata? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [athina-evals trust report](/tools/athina-ai-athina-evals/trust); [netdata trust report](/tools/netdata-netdata/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=athina-ai-athina-evals`](/api/graphcanon/graph?tool=athina-ai-athina-evals) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_