Comparison
harmonia vs awesome-AutoML
Verdict
Pick harmonia if harmonia supports federated learning with differential privacy modules and GitOps-inspired architecture, designed for both research and production usage; pick awesome-AutoML if curates AutoML research across neural architecture search, hyperparameter optimization, and meta-learning.
Markdown twin · harmonia alternatives · awesome-AutoML alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | harmonia | awesome-AutoML |
|---|---|---|
| Maintenance | Dormant (2143d since push) As of 2w · github_public_v1 | Slowing (133d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Personal account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- harmonia
- Federated Learning Made Easy
- awesome-AutoML
- Curating AutoML research and resources
Stars
- harmonia
- 17
- awesome-AutoML
- 941
Forks
- harmonia
- 14
- awesome-AutoML
- 156
Open issues
- harmonia
- 0
- awesome-AutoML
- 1
Language
- harmonia
- Go
- awesome-AutoML
- -
Adopt for
- harmonia
- Harmonia supports federated learning with differential privacy modules and GitOps-inspired architecture, designed for both research and production usage.
- awesome-AutoML
- Curates AutoML research across neural architecture search, hyperparameter optimization, and meta-learning.
Persona
- harmonia
- -
- awesome-AutoML
- -
Runtime
- harmonia
- -
- awesome-AutoML
- -
License
- harmonia
- MPL-2.0
- awesome-AutoML
- GPL-3.0
Last pushed
- harmonia
- Sep 21, 2020
- awesome-AutoML
- Mar 24, 2026
Categories
- harmonia
- Model Training
- awesome-AutoML
- Model Training
Trust and health
Maintenance
- harmonia
- Dormant (18%)
- awesome-AutoML
- Slowing (36%)
Days since push
- harmonia
- 2143d
- awesome-AutoML
- 133d
Open issues (now)
- harmonia
- 0
- awesome-AutoML
- 1
Owner type
- harmonia
- Organization
- awesome-AutoML
- User
Full report
- harmonia
- Trust report
- awesome-AutoML
- Trust report
Choose harmonia if…
- License: harmonia is MPL-2.0, awesome-AutoML is GPL-3.0.
- Tags unique to harmonia: differential privacy, federated-learning, gitops.
- When needing frameworks that incorporate differential privacy directly into federated learning processes
When NOT to use harmonia
- If GitOps-inspired workflows are not aligned with your team's operational practices
- In scenarios where the use of Go is less preferred among development teams
Choose awesome-AutoML if…
- License: awesome-AutoML is GPL-3.0, harmonia is MPL-2.0.
- Tags unique to awesome-AutoML: automl, hyperparameter-optimization, meta-learning, neural-architecture-search.
- When seeking comprehensive resources on diverse AutoML topics from recent and impactful research.
When NOT to use awesome-AutoML
- If looking for direct implementation advice as the repository focuses more on linking to resources rather than providing specific how-to guides.
- When requiring real-time or interactive AutoML features, since it's a curation hub rather than an application tool.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (ailabstw/harmonia) · observed Aug 4, 2026
- GitHub forks (ailabstw/harmonia) · observed Aug 4, 2026
- Last push (ailabstw/harmonia) · observed Sep 21, 2020
- License file (MPL-2.0) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (windmaple/awesome-AutoML) · observed Aug 4, 2026
- GitHub forks (windmaple/awesome-AutoML) · observed Aug 4, 2026
- Last push (windmaple/awesome-AutoML) · observed Mar 24, 2026
- License file (GPL-3.0) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: harmonia 17 · awesome-AutoML 941 (synced Aug 4, 2026).
Common questions
- What is the difference between harmonia and awesome-AutoML?
- harmonia: Federated Learning Made Easy. awesome-AutoML: Curating AutoML research and resources. See the comparison table for live GitHub stats and shared categories.
- When should I choose harmonia over awesome-AutoML?
- Choose harmonia over awesome-AutoML when License: harmonia is MPL-2.0, awesome-AutoML is GPL-3.0; Tags unique to harmonia: differential privacy, federated-learning, gitops; When needing frameworks that incorporate differential privacy directly into federated learning processes.
- When should I choose awesome-AutoML over harmonia?
- Choose awesome-AutoML over harmonia when License: awesome-AutoML is GPL-3.0, harmonia is MPL-2.0; Tags unique to awesome-AutoML: automl, hyperparameter-optimization, meta-learning, neural-architecture-search; When seeking comprehensive resources on diverse AutoML topics from recent and impactful research.
- When should I avoid harmonia?
- If GitOps-inspired workflows are not aligned with your team's operational practices In scenarios where the use of Go is less preferred among development teams
- When should I avoid awesome-AutoML?
- If looking for direct implementation advice as the repository focuses more on linking to resources rather than providing specific how-to guides. When requiring real-time or interactive AutoML features, since it's a curation hub rather than an application tool.
- Is harmonia or awesome-AutoML more popular on GitHub?
- awesome-AutoML has more GitHub stars (941 vs 17). Stars measure visibility, not whether either tool fits your constraints.
- Are harmonia and awesome-AutoML open source?
- Yes - both are open-source projects on GitHub (harmonia: MPL-2.0, awesome-AutoML: GPL-3.0).
- Where can I find alternatives to harmonia or awesome-AutoML?
- GraphCanon lists graph-backed alternatives at harmonia alternatives and awesome-AutoML alternatives (harmonia markdown twin, awesome-AutoML 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, harmonia or awesome-AutoML?
- harmonia: Dormant. awesome-AutoML: Slowing. 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 harmonia and awesome-AutoML?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: harmonia trust report; awesome-AutoML trust report.