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Efficient collaboration
without data duplication
Using folder names to version unstructured data is bad for collaboration. Version control of your data with commits and branches in the same dataset instead of copying the same data to different folders to work with them separately.
Version Control and Collaboration with a Git-like Structure
Role-based access control
Role-based access control(RBAC) is at the dataset-per-user level. Datasets can be shared with links for collaboration.
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Trackable dataset versioning
Dataset versioning is at dataset level for efficient collaboration through commits and branches. It is incremental with no data duplication.
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Comparable version differences
Compare different commits through visualization or by code.Track both the changes of raw data and dimensionality, while semantics (mostly annotations) of the same raw data can be compared side by side.
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Separation of read and write
With drafts introduced to data versioning, all commits are read-only and can be accessed concurrently while only one person can write to a draft before it gets committed.
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Explore more use cases
Data Curation
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Workflow Automation
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