--- title: "databuff vs moby" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/databufflabs-databuff-vs-moby-moby" tools: ["databufflabs-databuff", "moby-moby"] --- # databuff vs moby *GraphCanon updated Jul 15, 2026* ## Verdict Pick databuff when databuff is primarily Java; moby is Go; pick moby when moby is primarily Go; databuff is Java. [databuff](https://databuff.ai) reports 309 GitHub stars, 60 forks, and 12 open issues, last pushed Jul 15, 2026. [moby](https://mobyproject.org/) has 72k stars, 19k forks, and 3.8k open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [databuff's repository](https://github.com/databufflabs/databuff) and [moby's repository](https://github.com/moby/moby). | | [databuff](/tools/databufflabs-databuff.md) | [moby](/tools/moby-moby.md) | | --- | --- | --- | | Tagline | AI-native OpenTelemetry APM with multi-agent root-cause analysis across traces, metrics, and service topology | The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems | | Stars | 309 | 71,899 | | Forks | 60 | 19,126 | | Open issues | 12 | 3,821 | | Language | Java | Go | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | AGPL-3.0 | Apache-2.0 | | Categories | AI Agents, Inference & Serving, LLM Frameworks | Developer Tools, Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [databuff](/tools/databufflabs-databuff.md) | [moby](/tools/moby-moby.md) | | --- | --- | --- | | Days since push | 0d | 1d | | Open issues (now) | 12 | 3.8k | | Owner type | User | Organization | | Full report | [trust report](/tools/databufflabs-databuff/trust.md) | [trust report](/tools/moby-moby/trust.md) | ## Choose when ### Choose databuff if… - databuff is primarily Java; moby is Go. - License: databuff is AGPL-3.0, moby is Apache-2.0. - Tags unique to databuff: ai, ai-native, aiops, apm. - Also covers AI Agents. ### Choose moby if… - moby is primarily Go; databuff is Java. - License: moby is Apache-2.0, databuff is AGPL-3.0. - Tags unique to moby: containers, docker, go, golang. - Also covers Developer Tools. - moby ships Docker support for self-hosted deployment. ## When NOT to use databuff - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use moby - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between databuff and moby? databuff: AI-native OpenTelemetry APM with multi-agent root-cause analysis across traces, metrics, and service topology. moby: The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems. See the comparison table for live GitHub stats and shared categories. ### When should I choose databuff over moby? Choose databuff over moby when databuff is primarily Java; moby is Go; License: databuff is AGPL-3.0, moby is Apache-2.0; Tags unique to databuff: ai, ai-native, aiops, apm; Also covers AI Agents. ### When should I choose moby over databuff? Choose moby over databuff when moby is primarily Go; databuff is Java; License: moby is Apache-2.0, databuff is AGPL-3.0; Tags unique to moby: containers, docker, go, golang; Also covers Developer Tools; moby ships Docker support for self-hosted deployment. ### When should I avoid databuff? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid moby? Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is databuff or moby more popular on GitHub? moby has more GitHub stars (71,899 vs 309). Stars measure visibility, not whether either tool fits your constraints. ### Are databuff and moby open source? Yes - both are open-source projects on GitHub (databuff: AGPL-3.0, moby: Apache-2.0). ### Where can I find alternatives to databuff or moby? GraphCanon lists graph-backed alternatives at [databuff alternatives](/tools/databufflabs-databuff/alternatives) and [moby alternatives](/tools/moby-moby/alternatives) ([databuff markdown twin](/tools/databufflabs-databuff/alternatives.md), [moby markdown twin](/tools/moby-moby/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/databufflabs-databuff-vs-moby-moby.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, databuff or moby? databuff: Very active. moby: 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 databuff and moby? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [databuff trust report](/tools/databufflabs-databuff/trust); [moby trust report](/tools/moby-moby/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=databufflabs-databuff`](/api/graphcanon/graph?tool=databufflabs-databuff) - 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/_