Comparison
hopsworks vs mlflow
Verdict
Pick hopsworks if hopsworks, an ML platform with robust data management and model serving capabilities, supports multiple cloud environments like AWS, Azure, and GCP; 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,.
Markdown twin · hopsworks alternatives · mlflow alternatives
GraphCanon updated 4d
Trust & integrity
| Signal | hopsworks | mlflow |
|---|---|---|
| Maintenance | Dormant (539d since push) As of 3w · github_public_v1 | Very active (0d since push) As of 4d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 4d · 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
- hopsworks
- Data-Intensive AI platform with Feature Store
- mlflow
- AI engineering platform for debugging, evaluating, monitoring, and optimizing AI applications
Stars
- hopsworks
- 1.3k
- mlflow
- 28k
Forks
- hopsworks
- 160
- mlflow
- 6.2k
Open issues
- hopsworks
- 16
- mlflow
- 2.1k
Language
- hopsworks
- Java
- mlflow
- Python
Adopt for
- hopsworks
- Hopsworks, an ML platform with robust data management and model serving capabilities, supports multiple cloud environments like AWS, Azure, and GCP.
- 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,
Persona
- hopsworks
- -
- mlflow
- -
Runtime
- hopsworks
- -
- mlflow
- -
License
- hopsworks
- AGPL-3.0
- mlflow
- Apache-2.0
Last pushed
- hopsworks
- Feb 10, 2025
- mlflow
- Aug 20, 2026
Categories
- hopsworks
- Evaluation & Observability, Inference & Serving, Model Training
- mlflow
- Evaluation & Observability, Inference & Serving, Model Training
Trust and health
Maintenance
- hopsworks
- Dormant (18%)
- mlflow
- Very active (96%)
Days since push
- hopsworks
- 539d
- mlflow
- 0d
Open issues (now)
- hopsworks
- 16
- mlflow
- 2.1k
Stars delta
- hopsworks
- Unknown
- mlflow
- +476 (30d)
Open issues delta
- hopsworks
- Unknown
- mlflow
- -22 (30d)
Full report
- hopsworks
- Trust report
- mlflow
- Trust report
Choose hopsworks if…
- hopsworks is primarily Java; mlflow is Python.
- License: hopsworks is AGPL-3.0, mlflow is Apache-2.0.
- Tags unique to hopsworks: aws, azure, feature-store, gcp.
- When project requirements include a comprehensive feature store for AI applications
When NOT to use hopsworks
- If developers prefer a tool requiring less computational resources to install
- In scenarios where the preferred language is not Java and compatibility is an issue
Choose mlflow if…
- mlflow is primarily Python; hopsworks is Java.
- License: mlflow is Apache-2.0, hopsworks is AGPL-3.0.
- Tags unique to mlflow: agentops, agents, ai-governance, evaluation.
- - 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (logicalclocks/hopsworks) · observed Aug 3, 2026
- GitHub forks (logicalclocks/hopsworks) · observed Aug 3, 2026
- Last push (logicalclocks/hopsworks) · observed Feb 10, 2025
- License file (AGPL-3.0) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (mlflow/mlflow) · observed Aug 20, 2026
- GitHub forks (mlflow/mlflow) · observed Aug 20, 2026
- Last push (mlflow/mlflow) · observed Aug 20, 2026
- License file (Apache-2.0) · observed Aug 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: hopsworks 1.3k · mlflow 28k (synced Aug 3, 2026).
Common questions
- What is the difference between hopsworks and mlflow?
- hopsworks: Data-Intensive AI platform with Feature Store. mlflow: AI engineering platform for debugging, evaluating, monitoring, and optimizing AI applications. See the comparison table for live GitHub stats and shared categories.
- When should I choose hopsworks over mlflow?
- Choose hopsworks over mlflow when hopsworks is primarily Java; mlflow is Python; License: hopsworks is AGPL-3.0, mlflow is Apache-2.0; Tags unique to hopsworks: aws, azure, feature-store, gcp; When project requirements include a comprehensive feature store for AI applications.
- When should I choose mlflow over hopsworks?
- Choose mlflow over hopsworks when mlflow is primarily Python; hopsworks is Java; License: mlflow is Apache-2.0, hopsworks is AGPL-3.0; Tags unique to mlflow: agentops, agents, ai-governance, evaluation; - Use when you're working with a diverse range of environments like local or cloud platforms because MLflow is **vendor-neutral**.
- When should I avoid hopsworks?
- If developers prefer a tool requiring less computational resources to install In scenarios where the preferred language is not Java and compatibility is an issue
- 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.
- Is hopsworks or mlflow more popular on GitHub?
- mlflow has more GitHub stars (27,591 vs 1,302). Stars measure visibility, not whether either tool fits your constraints.
- Are hopsworks and mlflow open source?
- Yes - both are open-source projects on GitHub (hopsworks: AGPL-3.0, mlflow: Apache-2.0).
- Where can I find alternatives to hopsworks or mlflow?
- GraphCanon lists graph-backed alternatives at hopsworks alternatives and mlflow alternatives (hopsworks markdown twin, mlflow 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, hopsworks or mlflow?
- hopsworks: Dormant. mlflow: Very active. 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 hopsworks and mlflow?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: hopsworks trust report; mlflow trust report.