MLflow
DatabricksAI engineering platform covering the machine-learning and LLM lifecycle in one tool, combining distributed tracing of agents and model calls, automated evaluation, a prompt registry and an AI gateway with the experiment tracking and model registry it began as. Databricks Managed MLflow is sold beside it as hosting rather than as a paid tier.
The product entry does not declare its GitHub repository, so adoption is read through PyPI only.
Openness
5 high confidence- license
- Apache-2.0
- source
- public
- core features withheld
- no
Apache-2.0 across a fully published core; Databricks Managed MLflow is third-party hosting rather than a gated core.
- https://github.com/mlflow/mlflow recorded 2026-08-13
Repository page for the published platform. 27,501 stars, source public, one root license.
- https://github.com/mlflow/mlflow/blob/master/LICENSE.txt recorded 2026-08-13
The LICENSE file body, read rather than assumed. It carries the Databricks copyright line followed by the Apache License Version 2.0 text in full, including the "How to apply the Apache License to your work" appendix.
- https://mlflow.org/docs/latest/genai/tracing/ recorded 2026-09-29
Tracing docs: "MLflow Tracing gives you complete visibility into your agents and LLM applications." and "MLflow is open source and 100% FREE."
- https://mlflow.org/docs/latest/self-hosting/ recorded 2026-09-29
Self-hosting docs: "MLflow is fully open-source. Thousands of users and organizations run their own MLflow instances to meet their specific needs." Searched the body for license key, enterprise and paid tier: none.
- https://mlflow.org/genai/ recorded 2026-09-29
Product page: "100% open source under Apache 2.0 license. Forever free, no strings attached." with a schema.org license of Apache-2.0 and no paid tier named.
Adoption
5 high confidenceAdoption is measured by PyPI downloads of the mlflow package. MLflow began as an open experiment-tracking and model-registry platform and has since added distributed tracing, evaluation and prompt management for LLMs and agents, broadening the base that the download count reflects.
- https://github.com/mlflow/mlflow recorded 2026-08-13
mlflow/mlflow repository live, 27,501 stars
- https://pypistats.org/api/packages/mlflow/recent recorded 2026-08-13
{"data":{"last_day":1564540,"last_month":42050608,"last_week":10170289},"package":"mlflow","type":"recent_downloads"}
Capability
4 high confidenceA single open platform combining distributed tracing, prompt versioning, automated evaluation and trace replay for agents and LLMs on top of classic ML experiment tracking. There is no standard benchmark for observability, so this reading is set on its feature set, and MLflow sits level with Langfuse - the two of them are the pair the rest of this category is placed against.
- https://mlflow.org/docs/latest/genai/tracing/ recorded 2026-09-29
Tracing docs: "MLflow Tracing gives you complete visibility into your agents and LLM applications." and "MLflow is open source and 100% FREE."
- https://mlflow.org/genai/ recorded 2026-09-29
GenAI page: "Built-in observability, evaluation, prompt management, and monitoring. 100+ integrations" and "production-grade tracing, evaluation, prompt management, and much more".
Verified 2026-09-24