Comparison
harbor vs starwhale
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.
Markdown twin · harbor alternatives · starwhale alternatives
GraphCanon updated Sep 29, 2026
9views this month
Trust & integrity
| Signal | harbor | starwhale |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 20, 2026 · github_public_v1 | Dormant (648d since push) As of Sep 29, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 29, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- harbor
- Complete pre-wired LLM stack via one command
- starwhale
- an MLOps/LLMOps platform
Stars
- harbor
- 3.2k
- starwhale
- 236
Forks
- harbor
- 227
- starwhale
- 37
Open issues
- harbor
- 67
- starwhale
- 120
Language
- harbor
- Python
- starwhale
- Java
Adopt for
- harbor
- Harbor is a rapid deployment tool for AI stacks using Docker and docker-compose.
- starwhale
- Starwhale is an MLOps/LLMOps platform that focuses on model management for AI and large language models through various runtime setups.
Persona
- harbor
- -
- starwhale
- -
Runtime
- harbor
- -
- starwhale
- -
License
- harbor
- Apache-2.0
- starwhale
- Starwhale uses the Apache License 2.0, which is permissive and allows for usage in both open source and commercial applications with attribution.
Last pushed
- harbor
- Sep 19, 2026
- starwhale
- Dec 20, 2024
Categories
- harbor
- Inference & Serving, LLM Frameworks, Model Training
- starwhale
- Data & Retrieval, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training
Trust and health
Maintenance
- harbor
- Very active (96%)
- starwhale
- Dormant (18%)
Days since push
- harbor
- 0d
- starwhale
- 648d
Open issues (now)
- harbor
- 67
- starwhale
- 120
Stars delta
- harbor
- +55 (30d)
- starwhale
- -1 (30d)
Open issues delta
- harbor
- +3 (30d)
- starwhale
- 0 (30d)
Owner type
- harbor
- User
- starwhale
- Organization
Full report
- harbor
- Trust report
- starwhale
- Trust report
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
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
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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (av/harbor) · observed Sep 20, 2026
- GitHub forks (av/harbor) · observed Sep 20, 2026
- Last push (av/harbor) · observed Sep 19, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (star-whale/starwhale) · observed Sep 29, 2026
- GitHub forks (star-whale/starwhale) · observed Sep 29, 2026
- Last push (star-whale/starwhale) · observed Dec 20, 2024
- License file (Apache-2.0) · observed Sep 29, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: harbor 3.2k · starwhale 236 (synced Sep 20, 2026).
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 (3,217 vs 236). 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 and starwhale alternatives (harbor markdown twin, starwhale markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, harbor or starwhale?
- harbor: Very 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; starwhale trust report.