--- title: "hopsworks vs mlflow" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/logicalclocks-hopsworks-vs-mlflow-mlflow" tools: ["logicalclocks-hopsworks", "mlflow-mlflow"] --- # hopsworks vs mlflow *GraphCanon updated Aug 20, 2026* ## 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,. [hopsworks](https://hopsworks.ai) reports 1.3k GitHub stars, 160 forks, and 16 open issues, last pushed Feb 10, 2025. [mlflow](https://mlflow.org) has 28k stars, 6.2k forks, and 2.1k open issues, last pushed Aug 20, 2026. Figures are from public GitHub metadata via [hopsworks's repository](https://github.com/logicalclocks/hopsworks) and [mlflow's repository](https://github.com/mlflow/mlflow). | | [hopsworks](/tools/logicalclocks-hopsworks.md) | [mlflow](/tools/mlflow-mlflow.md) | | --- | --- | --- | | Tagline | Data-Intensive AI platform with Feature Store | AI engineering platform for debugging, evaluating, monitoring, and optimizing AI applications | | Stars | 1,302 | 27,591 | | Forks | 160 | 6,189 | | Open issues | 16 | 2,054 | | Language | Java | Python | | Adopt for | Hopsworks, an ML platform with robust data management and model serving capabilities, supports multiple cloud environments like AWS, Azure, and GCP. | 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 | - | - | | Runtime | - | - | | License | AGPL-3.0 | Apache-2.0 | | Categories | Evaluation & Observability, Inference & Serving, Model Training | Evaluation & Observability, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [hopsworks](/tools/logicalclocks-hopsworks.md) | [mlflow](/tools/mlflow-mlflow.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 539d | 0d | | Open issues (now) | 16 | 2.1k | | Stars delta | Unknown | +476 (30d) | | Open issues delta | Unknown | -22 (30d) | | Full report | [trust report](/tools/logicalclocks-hopsworks/trust.md) | [trust report](/tools/mlflow-mlflow/trust.md) | ## Decision facts: hopsworks - **Adopt for:** Hopsworks, an ML platform with robust data management and model serving capabilities, supports multiple cloud environments like AWS, Azure, and GCP. ## Decision facts: mlflow - **Adopt for:** 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, ## Choose when ### 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 ### 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 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 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. ## 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](/tools/logicalclocks-hopsworks/alternatives) and [mlflow alternatives](/tools/mlflow-mlflow/alternatives) ([hopsworks markdown twin](/tools/logicalclocks-hopsworks/alternatives.md), [mlflow markdown twin](/tools/mlflow-mlflow/alternatives.md)), 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](/compare/logicalclocks-hopsworks-vs-mlflow-mlflow.md) 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](/tools/logicalclocks-hopsworks/trust); [mlflow trust report](/tools/mlflow-mlflow/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=logicalclocks-hopsworks`](/api/graphcanon/graph?tool=logicalclocks-hopsworks) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_