Alternatives to Mlflow
6 alternatives found
MLflow is an open-source platform for managing the full machine learning lifecycle, created by Databricks in 2018 and now one of the most widely adopted MLOps tools with over 17 million monthly downloads. MLflow's four core components address the key pain points of ML teams: Tracking (log experiments, parameters, metrics, and artifacts), Projects (package ML code for reproducibility), Models (a standard format for packaging models deployable to any serving platform), and Model Registry (centralized model store with versioning, stage transitions, and approval workflows).
Weights & Biases
Richer experiment visualization and collaboration features — preferred for deep learning teams
DVC
Git-based data and model versioning — complementary to MLflow Tracking for dataset lineage
Neptune
Managed experiment tracking with stronger team collaboration and metadata querying
Kubeflow
Kubernetes-native ML pipelines — MLflow for tracking, Kubeflow for orchestration at scale
SageMaker
AWS end-to-end ML platform — managed training and deployment, MLflow integrates as tracking layer
Dagster
Asset-centric orchestration — Dagster can orchestrate MLflow experiment runs in ML pipelines
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