DVC (Data Version Control) is an open-source version control system specifically designed for handling machine learning projects. It allows you to version datasets, models, and code in a Git-like fashion while handling large files efficiently.

MLflow is an open-source platform that includes components for tracking and managing experiments, packaging code into reproducible runs, and managing models. MLflow Tracking can be used for versioning datasets and tracking experiments.

Pachyderm is a data versioning tool that integrates with Git and allows versioning data repositories. It provides features for data lineage, data provenance, and managing the evolution of datasets over time.

Kaggle Datasets is a platform for sharing and versioning datasets. While it's primarily associated with Kaggle competitions, it can also be used as a collaborative tool for versioning datasets.