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The key difference between MLflow and neptune.ai on a shallow level is really that neptune.ai does not offer a standalone OSS solution. Apart from that, its offering overlaps with MLflow's in the sense that it focuses on experiment tracking (incl. metadata store) as well as model artifact management ("model registry"). Of course, there' lots of differences in the detail then. However, since I've never used neptune.ai, I cannot really comment on that.
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a more popular project.