--- title: "arthas vs feast" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/alibaba-arthas-vs-feast-dev-feast" tools: ["alibaba-arthas", "feast-dev-feast"] --- # arthas vs feast *GraphCanon updated Jul 11, 2026* ## Verdict Pick arthas when arthas is primarily Java; feast is Python; pick feast when feast is primarily Python; arthas is Java. [arthas](https://arthas.aliyun.com/) reports 37k GitHub stars, 7.6k forks, and 485 open issues, last pushed Jul 1, 2026. [feast](https://feast.dev) has 7.1k stars, 1.4k forks, and 389 open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [arthas's repository](https://github.com/alibaba/arthas) and [feast's repository](https://github.com/feast-dev/feast). | | [arthas](/tools/alibaba-arthas.md) | [feast](/tools/feast-dev-feast.md) | | --- | --- | --- | | Tagline | Alibaba Java Diagnostic Tool Arthas | The Open Source Feature Store for AI/ML | | Stars | 37,427 | 7,127 | | Forks | 7,634 | 1,360 | | Open issues | 485 | 389 | | Language | Java | Python | | Adopt for | Arthas is a Java diagnostic tool from Alibaba designed to monitor and troubleshoot running Java applications using features such as tracing, classloader analysis, and JVM diagnostics. | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Developer Tools | Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [arthas](/tools/alibaba-arthas.md) | [feast](/tools/feast-dev-feast.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 10d | 1d | | Open issues (now) | 485 | 389 | | Security scan | No lockfile | 38 low (38 low) | | Full report | [trust report](/tools/alibaba-arthas/trust.md) | [trust report](/tools/feast-dev-feast/trust.md) | ## Decision facts: arthas - **Requirements:** Min 1 GB RAM - **Adopt for:** Arthas is a Java diagnostic tool from Alibaba designed to monitor and troubleshoot running Java applications using features such as tracing, classloader analysis, and JVM diagnostics. ## Choose when ### Choose arthas if… - arthas is primarily Java; feast is Python. - Requirements: Min 1 GB RAM. - Tags unique to arthas: diagnosis, jvm, trouble-shooting, java. - arthas ships Docker support for self-hosted deployment. - Utilize Arthas for deep diagnostics on running Java applications where you need advanced features such as bytecode enhancement or specific trace capabilities over static analysis. ### Choose feast if… - feast is primarily Python; arthas is Java. - Tags unique to feast: data-science, ml, features, big-data. - More recently updated (last pushed Jul 10, 2026). ## When NOT to use arthas - Avoid using Arthas if your primary need is for quick, surface-level diagnostics or performance tuning without diving into more advanced features. - Do not use Arthas if you are working in a development environment outside of Java where this specific diagnostic tool would provide no value. ## When NOT to use feast - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. ## Common questions ### What is the difference between arthas and feast? arthas: Alibaba Java Diagnostic Tool Arthas. feast: The Open Source Feature Store for AI/ML. See the comparison table for live GitHub stats and shared categories. ### When should I choose arthas over feast? Choose arthas over feast when arthas is primarily Java; feast is Python; Requirements: Min 1 GB RAM; Tags unique to arthas: diagnosis, jvm, trouble-shooting, java; arthas ships Docker support for self-hosted deployment; Utilize Arthas for deep diagnostics on running Java applications where you need advanced features such as bytecode enhancement or specific trace capabilities over static analysis. ### When should I choose feast over arthas? Choose feast over arthas when feast is primarily Python; arthas is Java; Tags unique to feast: data-science, ml, features, big-data; More recently updated (last pushed Jul 10, 2026). ### When should I avoid arthas? Avoid using Arthas if your primary need is for quick, surface-level diagnostics or performance tuning without diving into more advanced features. Do not use Arthas if you are working in a development environment outside of Java where this specific diagnostic tool would provide no value. ### When should I avoid feast? Developer Tools: A gateway is overkill when you're pinned to a single provider and model. ### Is arthas or feast more popular on GitHub? arthas has more GitHub stars (37,427 vs 7,127). Stars measure visibility, not whether either tool fits your constraints. ### Are arthas and feast open source? Yes - both are open-source projects on GitHub (arthas: Apache-2.0, feast: Apache-2.0). ### Where can I find alternatives to arthas or feast? GraphCanon lists graph-backed alternatives at [arthas alternatives](/tools/alibaba-arthas/alternatives) and [feast alternatives](/tools/feast-dev-feast/alternatives) ([arthas markdown twin](/tools/alibaba-arthas/alternatives.md), [feast markdown twin](/tools/feast-dev-feast/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/alibaba-arthas-vs-feast-dev-feast.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, arthas or feast? arthas: Active. feast: 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 arthas and feast? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [arthas trust report](/tools/alibaba-arthas/trust); [feast trust report](/tools/feast-dev-feast/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=alibaba-arthas`](/api/graphcanon/graph?tool=alibaba-arthas) - 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/_