Comparison
graph vs awesome-mlops
Verdict
Pick graph when pricing: Free and open-source under the MIT license.; pick awesome-mlops when tags unique to awesome-mlops: engineering, data-science, ml, ai.
Markdown twin · graph alternatives · awesome-mlops alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | graph | awesome-mlops |
|---|---|---|
| Maintenance | Very active (0d since push) As of today · github_public_v1 | Dormant (597d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Personal account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- graph
- GPU-accelerated force graph layout and rendering
- awesome-mlops
- A curated list of references for MLOps
Stars
- graph
- 1.2k
- awesome-mlops
- 14k
Forks
- graph
- 83
- awesome-mlops
- 2.1k
Open issues
- graph
- 18
- awesome-mlops
- 42
Language
- graph
- TypeScript
- awesome-mlops
- -
Adopt for
- graph
- CosmosGL/graph provides GPU-accelerated techniques for creating and rendering force-directed layouts. This makes it particularly apt for users who need to visualize complex networks efficiently.
- awesome-mlops
- -
Persona
- graph
- -
- awesome-mlops
- -
Runtime
- graph
- -
- awesome-mlops
- -
License
- graph
- MIT License
- awesome-mlops
- -
Last pushed
- graph
- Jul 11, 2026
- awesome-mlops
- Nov 21, 2024
Categories
- graph
- Data & Retrieval, Vector Databases
- awesome-mlops
- Model Training, Vector Databases, Inference & Serving
Trust and health
Maintenance
- graph
- Very active (96%)
- awesome-mlops
- Dormant (18%)
Days since push
- graph
- 0d
- awesome-mlops
- 597d
Open issues (now)
- graph
- 18
- awesome-mlops
- 42
Owner type
- graph
- Organization
- awesome-mlops
- User
Full report
- graph
- Trust report
- awesome-mlops
- Trust report
Choose graph if…
- Pricing: Free and open-source under the MIT license..
- Requirements: Requires a WebGL-supported environment.
- Tags unique to graph: force, webgl, embeddings, graph.
- Also covers Data & Retrieval.
- - When you require rapid visualization of large, complex network structures due to its GPU acceleration
When NOT to use graph
- - If your project does not involve visualizing complex networks as this tool's forte lies in force-directed graphical representations
- - When working with systems or frameworks that do not support WebGL, since CosmosGL/graph relies on it for rendering
Choose awesome-mlops if…
- Tags unique to awesome-mlops: engineering, data-science, ml, ai.
- Also covers Model Training, Inference & Serving.
- More GitHub stars (14k vs 1.2k) - visibility, not fit.
When NOT to use awesome-mlops
- Last GitHub push was 597 days ago (dormant maintenance, Nov 21, 2024). Validate activity before betting a new project on awesome-mlops.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (cosmosgl/graph) · observed Jul 11, 2026
- GitHub forks (cosmosgl/graph) · observed Jul 11, 2026
- Last push (cosmosgl/graph) · observed Jul 11, 2026
- License file (MIT) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (visenger/awesome-mlops) · observed Jul 11, 2026
- GitHub forks (visenger/awesome-mlops) · observed Jul 11, 2026
- Last push (visenger/awesome-mlops) · observed Nov 21, 2024
- License file (unknown) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: graph 1.2k · awesome-mlops 14k (synced Jul 11, 2026).
Common questions
- What is the difference between graph and awesome-mlops?
- graph: GPU-accelerated force graph layout and rendering. awesome-mlops: A curated list of references for MLOps. See the comparison table for live GitHub stats and shared categories.
- When should I choose graph over awesome-mlops?
- Choose graph over awesome-mlops when Pricing: Free and open-source under the MIT license.; Requirements: Requires a WebGL-supported environment; Tags unique to graph: force, webgl, embeddings, graph; Also covers Data & Retrieval; - When you require rapid visualization of large, complex network structures due to its GPU acceleration.
- When should I choose awesome-mlops over graph?
- Choose awesome-mlops over graph when Tags unique to awesome-mlops: engineering, data-science, ml, ai; Also covers Model Training, Inference & Serving; More GitHub stars (14k vs 1.2k) - visibility, not fit.
- When should I avoid graph?
- - If your project does not involve visualizing complex networks as this tool's forte lies in force-directed graphical representations - When working with systems or frameworks that do not support WebGL, since CosmosGL/graph relies on it for rendering
- When should I avoid awesome-mlops?
- Last GitHub push was 597 days ago (dormant maintenance, Nov 21, 2024). Validate activity before betting a new project on awesome-mlops. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- Is graph or awesome-mlops more popular on GitHub?
- awesome-mlops has more GitHub stars (13,952 vs 1,193). Stars measure visibility, not whether either tool fits your constraints.
- Are graph and awesome-mlops open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to graph or awesome-mlops?
- GraphCanon lists graph-backed alternatives at graph alternatives and awesome-mlops alternatives (graph markdown twin, awesome-mlops 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, graph or awesome-mlops?
- graph: Very active. awesome-mlops: 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 graph and awesome-mlops?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: graph trust report; awesome-mlops trust report.