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Comparison

mlflow vs aqueduct

Verdict

Pick mlflow if mLflow is an open-source platform that offers comprehensive capabilities for managing, deploying, and monitoring machine learning models as well as large language models (LLMs) and AI agents. MLflow supports various use,; pick aqueduct if aqueduct is a deprecated Go-based tool for orchestrating LLM and ML workloads across various cloud infrastructures with Kubernetes support.

Markdown twin · mlflow alternatives · aqueduct alternatives

GraphCanon updated 4d

mlflow logo

mlflow

mlflow/mlflow

★ 28kpushed Aug 20, 2026
vs
aqueduct logo

aqueduct

RunLLM/aqueduct

★ 517pushed Jun 7, 2023

Trust & integrity

Signalmlflowaqueduct
Maintenance
Very active (0d since push)
As of 4d · github_public_v1
Dormant (1152d since push)
As of 3w · github_public_v1
Provenance
Not a fork · Organization account
As of 4d · github_public_v1
Not a fork · Organization account
As of 3w · 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
mlflow trust reportaqueduct trust reportTrust methodology

Tagline

mlflow
AI engineering platform for debugging, evaluating, monitoring, and optimizing AI applications
aqueduct
Orchestrate LLM and ML workloads on any cloud infrastructure using Go.

Stars

mlflow
28k
aqueduct
517

Forks

mlflow
6.2k
aqueduct
20

Open issues

mlflow
2.1k
aqueduct
11

Language

mlflow
Python
aqueduct
Go

Adopt for

mlflow
MLflow is an open-source platform that offers comprehensive capabilities for managing, deploying, and monitoring machine learning models as well as large language models (LLMs) and AI agents. MLflow supports various use,
aqueduct
Aqueduct is a deprecated Go-based tool for orchestrating LLM and ML workloads across various cloud infrastructures with Kubernetes support.

Persona

mlflow
-
aqueduct
-

Runtime

mlflow
-
aqueduct
-

License

mlflow
Apache-2.0
aqueduct
Apache-2.0

Last pushed

mlflow
Aug 20, 2026
aqueduct
Jun 7, 2023

Categories

mlflow
Evaluation & Observability, Inference & Serving, Model Training
aqueduct
Inference & Serving, LLM Frameworks, Model Training

Trust and health

Maintenance

mlflow
Very active (96%)
aqueduct
Dormant (18%)

Days since push

mlflow
0d
aqueduct
1152d

Open issues (now)

mlflow
2.1k
aqueduct
11

Stars delta

mlflow
+476 (30d)
aqueduct
Unknown

Open issues delta

mlflow
-22 (30d)
aqueduct
Unknown

Full report

mlflow
Trust report
aqueduct
Trust report

Choose mlflow if…

  • mlflow is primarily Python; aqueduct is Go.
  • Tags unique to mlflow: agentops, agents, ai-governance, evaluation.
  • Also covers Evaluation & Observability.
  • - Use when you're working with a diverse range of environments like local or cloud platforms because MLflow is **vendor-neutral**.

When NOT to use mlflow

  • - Avoid if your organization has strong preferences for proprietary solutions with advanced features not available in the open-source domain.
  • - Not recommended for users who prefer a fully managed service without self-hosting options, as competitors like Databricks or Azure ML offer integrated services tailored for their cloud environments.
GitHubDetails

Choose aqueduct if…

  • aqueduct is primarily Go; mlflow is Python.
  • Tags unique to aqueduct: ai, data, data-science, kubernetes.
  • Also covers LLM Frameworks.
  • When you need to deploy legacy workflows that depend on Aqueduct's specific implementation of custom ops for resource allocation and training.

When NOT to use aqueduct

  • Avoid if active project maintenance or community support is required as Aqueduct is no longer maintained.
  • Skip this tool for new projects focusing on state-of-the-art ML orchestration, opting instead for actively supported alternatives.
GitHubDetails

Explore

mlflow trust report →aqueduct trust report →Evaluation & Observability category →Inference & Serving category →Model Training category →LLM Frameworks category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: mlflow 28k · aqueduct 517 (synced Aug 20, 2026).

Common questions

What is the difference between mlflow and aqueduct?
mlflow: AI engineering platform for debugging, evaluating, monitoring, and optimizing AI applications. aqueduct: Orchestrate LLM and ML workloads on any cloud infrastructure using Go.. See the comparison table for live GitHub stats and shared categories.
When should I choose mlflow over aqueduct?
Choose mlflow over aqueduct when mlflow is primarily Python; aqueduct is Go; Tags unique to mlflow: agentops, agents, ai-governance, evaluation; Also covers Evaluation & Observability; - Use when you're working with a diverse range of environments like local or cloud platforms because MLflow is **vendor-neutral**.
When should I choose aqueduct over mlflow?
Choose aqueduct over mlflow when aqueduct is primarily Go; mlflow is Python; Tags unique to aqueduct: ai, data, data-science, kubernetes; Also covers LLM Frameworks; When you need to deploy legacy workflows that depend on Aqueduct's specific implementation of custom ops for resource allocation and training.
When should I avoid mlflow?
- Avoid if your organization has strong preferences for proprietary solutions with advanced features not available in the open-source domain. - Not recommended for users who prefer a fully managed service without self-hosting options, as competitors like Databricks or Azure ML offer integrated services tailored for their cloud environments.
When should I avoid aqueduct?
Avoid if active project maintenance or community support is required as Aqueduct is no longer maintained. Skip this tool for new projects focusing on state-of-the-art ML orchestration, opting instead for actively supported alternatives.
Is mlflow or aqueduct more popular on GitHub?
mlflow has more GitHub stars (27,591 vs 517). Stars measure visibility, not whether either tool fits your constraints.
Are mlflow and aqueduct open source?
Yes - both are open-source projects on GitHub (mlflow: Apache-2.0, aqueduct: Apache-2.0).
Where can I find alternatives to mlflow or aqueduct?
GraphCanon lists graph-backed alternatives at mlflow alternatives and aqueduct alternatives (mlflow markdown twin, aqueduct 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, mlflow or aqueduct?
mlflow: Very active. aqueduct: 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 mlflow and aqueduct?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: mlflow trust report; aqueduct trust report.

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