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Experiment tracking
Data versioning
Model registry
Artifact tracking

Neptune is a flexible metadata store for MLOps that allows teams to log, store, display, organize, compare, and query model-building metadata.

Use it when

  • You want a lightweight tool to cover data versioning, model registry, experiment, and artifact tracking.
  • You want to record and monitor model training, evaluation, or production runs.
  • You want a tool that covers a wide range of metadata types to log and display, from model parameters to audio and video files.
  • You want 25+ built-in integrations with popular Python libraries.

Watch out

  • Only the Neptune client is open-source and requires signing up.
  • The Neptune client covers data logging to the Neptune server, data queries, and downloads of your logged data.
  • The free plan is only for individual use up to 200 monitoring hours/month.
  • Self-hosted deployment requires an Organization plan.

Example stacks

Airflow + MLflow stack


pip install neptune-client