Comparison
awesome-mlops vs ormb
Verdict
Pick awesome-mlops if awesome MLOps is a curated list of tools encompassing AutoML to CI/CD for ML; pick ormb if oRMB encapsulates machine learning and deep-learning models via OCI artifacts within Docker containers for streamlined model management.
Markdown twin · awesome-mlops alternatives · ormb alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | awesome-mlops | ormb |
|---|---|---|
| Maintenance | Slowing (97d since push) As of 2w · github_public_v1 | Dormant (920d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2w · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings 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
- awesome-mlops
- A curated list of awesome MLOps tools.
- ormb
- Docker for ML/DL Models Based on OCI Artifacts
Stars
- awesome-mlops
- 5.2k
- ormb
- 473
Forks
- awesome-mlops
- 762
- ormb
- 61
Open issues
- awesome-mlops
- 71
- ormb
- 32
Language
- awesome-mlops
- Python
- ormb
- Go
Adopt for
- awesome-mlops
- Awesome MLOps is a curated list of tools encompassing AutoML to CI/CD for ML.
- ormb
- ORMB encapsulates machine learning and deep-learning models via OCI artifacts within Docker containers for streamlined model management.
Persona
- awesome-mlops
- -
- ormb
- -
Runtime
- awesome-mlops
- -
- ormb
- -
License
- awesome-mlops
- -
- ormb
- Apache-2.0
Last pushed
- awesome-mlops
- Apr 29, 2026
- ormb
- Jan 26, 2024
Categories
- awesome-mlops
- Developer Tools, Evaluation & Observability, Inference & Serving, Model Training
- ormb
- Inference & Serving, Model Training
Trust and health
Maintenance
- awesome-mlops
- Slowing (36%)
- ormb
- Dormant (18%)
Days since push
- awesome-mlops
- 97d
- ormb
- 920d
Open issues (now)
- awesome-mlops
- 71
- ormb
- 32
Owner type
- awesome-mlops
- User
- ormb
- Organization
OSV dependency advisories
- awesome-mlops
- No lockfile (source not queried)
- ormb
- Published findings
Full report
- awesome-mlops
- Trust report
- ormb
- Trust report
Choose awesome-mlops if…
- awesome-mlops is primarily Python; ormb is Go.
- Tags unique to awesome-mlops: ai, awesome, data-science, machine-learning-engineering.
- Also covers Developer Tools, Evaluation & Observability.
- You need resources across multiple facets of the machine-learning pipeline, from data validation to model serving.
When NOT to use awesome-mlops
- In search of a single comprehensive tool for end-to-end ML project management; Awesome MLOps is a repository of links rather than a standalone platform.
- Looking for proprietary solutions or detailed vendor-specific documentation as it focuses on broad, open-source offerings.
Choose ormb if…
- ormb is primarily Go; awesome-mlops is Python.
- Tags unique to ormb: docker, model-management, model-versioning, oci-artifacts.
- If you need sophisticated version control for your ML/DL models through an image registry, ORMB provides this functionality.
When NOT to use ormb
- Should you seek simple models deployment without extensive version management features, ORMB may introduce unnecessary complexity.
- If your project strictly avoids using Docker and OCI artifacts for model handling, then this tool would not be suitable.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (kelvins/awesome-mlops) · observed Aug 4, 2026
- GitHub forks (kelvins/awesome-mlops) · observed Aug 4, 2026
- Last push (kelvins/awesome-mlops) · observed Apr 29, 2026
- License file (unknown) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (kleveross/ormb) · observed Aug 4, 2026
- GitHub forks (kleveross/ormb) · observed Aug 4, 2026
- Last push (kleveross/ormb) · observed Jan 26, 2024
- License file (Apache-2.0) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: awesome-mlops 5.2k · ormb 473 (synced Aug 4, 2026).
Common questions
- What is the difference between awesome-mlops and ormb?
- awesome-mlops: A curated list of awesome MLOps tools.. ormb: Docker for ML/DL Models Based on OCI Artifacts. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-mlops over ormb?
- Choose awesome-mlops over ormb when awesome-mlops is primarily Python; ormb is Go; Tags unique to awesome-mlops: ai, awesome, data-science, machine-learning-engineering; Also covers Developer Tools, Evaluation & Observability; You need resources across multiple facets of the machine-learning pipeline, from data validation to model serving.
- When should I choose ormb over awesome-mlops?
- Choose ormb over awesome-mlops when ormb is primarily Go; awesome-mlops is Python; Tags unique to ormb: docker, model-management, model-versioning, oci-artifacts; If you need sophisticated version control for your ML/DL models through an image registry, ORMB provides this functionality.
- When should I avoid awesome-mlops?
- In search of a single comprehensive tool for end-to-end ML project management; Awesome MLOps is a repository of links rather than a standalone platform. Looking for proprietary solutions or detailed vendor-specific documentation as it focuses on broad, open-source offerings.
- When should I avoid ormb?
- Should you seek simple models deployment without extensive version management features, ORMB may introduce unnecessary complexity. If your project strictly avoids using Docker and OCI artifacts for model handling, then this tool would not be suitable.
- Is awesome-mlops or ormb more popular on GitHub?
- awesome-mlops has more GitHub stars (5,229 vs 473). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-mlops and ormb open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to awesome-mlops or ormb?
- GraphCanon lists graph-backed alternatives at awesome-mlops alternatives and ormb alternatives (awesome-mlops markdown twin, ormb 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, awesome-mlops or ormb?
- awesome-mlops: Slowing. ormb: 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 awesome-mlops and ormb?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-mlops trust report; ormb trust report.