--- title: "harbor vs starwhale" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/av-harbor-vs-star-whale-starwhale" tools: ["av-harbor", "star-whale-starwhale"] --- # harbor vs starwhale *GraphCanon updated Aug 11, 2026* ## Verdict Pick harbor if harbor is a rapid deployment tool for AI stacks using Docker and docker-compose; pick starwhale if starwhale is an MLOps/LLMOps platform that focuses on model management for AI and large language models through various runtime setups. [harbor](https://discord.gg/8nDRphrhSF) reports 3.2k GitHub stars, 220 forks, and 64 open issues, last pushed Aug 2, 2026. [starwhale](https://starwhale.ai) has 237 stars, 38 forks, and 120 open issues, last pushed Dec 20, 2024. Figures are from public GitHub metadata via [harbor's repository](https://github.com/av/harbor) and [starwhale's repository](https://github.com/star-whale/starwhale). | | [harbor](/tools/av-harbor.md) | [starwhale](/tools/star-whale-starwhale.md) | | --- | --- | --- | | Tagline | Complete pre-wired LLM stack via one command | an MLOps/LLMOps platform | | Stars | 3,162 | 237 | | Forks | 220 | 38 | | Open issues | 64 | 120 | | Language | Python | Java | | Adopt for | Harbor is a rapid deployment tool for AI stacks using Docker and docker-compose. | Starwhale is an MLOps/LLMOps platform that focuses on model management for AI and large language models through various runtime setups. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Starwhale uses the Apache License 2.0, which is permissive and allows for usage in both open source and commercial applications with attribution. | | Categories | Inference & Serving, LLM Frameworks, Model Training | Data & Retrieval, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [harbor](/tools/av-harbor.md) | [starwhale](/tools/star-whale-starwhale.md) | | --- | --- | --- | | Maintenance | Active (82%) | Dormant (18%) | | Days since push | 8d | 591d | | Open issues (now) | 64 | 120 | | Owner type | User | Organization | | Full report | [trust report](/tools/av-harbor/trust.md) | [trust report](/tools/star-whale-starwhale/trust.md) | ## Decision facts: harbor - **Adopt for:** Harbor is a rapid deployment tool for AI stacks using Docker and docker-compose. ## Decision facts: starwhale - **Requirements:** Requires Docker; Supports runtime builds through Docker images for compatibility across various system environments. - **Adopt for:** Starwhale is an MLOps/LLMOps platform that focuses on model management for AI and large language models through various runtime setups. - **License detail:** Starwhale uses the Apache License 2.0, which is permissive and allows for usage in both open source and commercial applications with attribution. ## Choose when ### Choose harbor if… - harbor is primarily Python; starwhale is Java. - Tags unique to harbor: automation, bash, cli, container. - - When you need to deploy an AI stack quickly with minimal configuration ### Choose starwhale if… - starwhale is primarily Java; harbor is Python. - Requirements: Requires Docker; Supports runtime builds through Docker images for compatibility across various system environments.. - Tags unique to starwhale: cloud-native, dataset, datastore, fine-tuning. - Also covers Data & Retrieval, Evaluation & Observability. - When the need arises to manage models across different runtimes, including local environment configurations via runtime.yaml or conda environments, Docker images, or shell commands. ## When NOT to use harbor - - If detailed customization at a service level is required beyond what the default setup offers - - In cases where the project does not align well with the pre-wired services and configurations harbor provides by default ## When NOT to use starwhale - In scenarios where an exclusive user preference leans towards Python-based operations over Java and the tool's CLI interactions do not meet operational demands. - For teams that require real-time model serving and have strict latency requirements, as Starwhale may not optimize for such use cases beyond its MLOps capabilities. ## Common questions ### What is the difference between harbor and starwhale? harbor: Complete pre-wired LLM stack via one command. starwhale: an MLOps/LLMOps platform. See the comparison table for live GitHub stats and shared categories. ### When should I choose harbor over starwhale? Choose harbor over starwhale when harbor is primarily Python; starwhale is Java; Tags unique to harbor: automation, bash, cli, container; - When you need to deploy an AI stack quickly with minimal configuration. ### When should I choose starwhale over harbor? Choose starwhale over harbor when starwhale is primarily Java; harbor is Python; Requirements: Requires Docker; Supports runtime builds through Docker images for compatibility across various system environments.; Tags unique to starwhale: cloud-native, dataset, datastore, fine-tuning; Also covers Data & Retrieval, Evaluation & Observability; When the need arises to manage models across different runtimes, including local environment configurations via runtime.yaml or conda environments, Docker images, or shell commands. ### When should I avoid harbor? - If detailed customization at a service level is required beyond what the default setup offers - In cases where the project does not align well with the pre-wired services and configurations harbor provides by default ### When should I avoid starwhale? In scenarios where an exclusive user preference leans towards Python-based operations over Java and the tool's CLI interactions do not meet operational demands. For teams that require real-time model serving and have strict latency requirements, as Starwhale may not optimize for such use cases beyond its MLOps capabilities. ### Is harbor or starwhale more popular on GitHub? harbor has more GitHub stars (3,162 vs 237). Stars measure visibility, not whether either tool fits your constraints. ### Are harbor and starwhale open source? Yes - both are open-source projects on GitHub (harbor: Apache-2.0, starwhale: Apache-2.0). ### Where can I find alternatives to harbor or starwhale? GraphCanon lists graph-backed alternatives at [harbor alternatives](/tools/av-harbor/alternatives) and [starwhale alternatives](/tools/star-whale-starwhale/alternatives) ([harbor markdown twin](/tools/av-harbor/alternatives.md), [starwhale markdown twin](/tools/star-whale-starwhale/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/av-harbor-vs-star-whale-starwhale.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, harbor or starwhale? harbor: Active. starwhale: Dormant. 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 harbor and starwhale? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [harbor trust report](/tools/av-harbor/trust); [starwhale trust report](/tools/star-whale-starwhale/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=av-harbor`](/api/graphcanon/graph?tool=av-harbor) - 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/_