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Data science teams often collaboratively analyze datasets, generating datasetversions at each stage of iterative exploration and analysis. There is apressing need for a system that can support dataset versioning, enabling suchteams to efficiently store, track, and query across dataset versions. Weintroduce OrpheusDB, a dataset version control system that "bolts on"versioning capabilities to a traditional relational database system, therebygaining the analytics capabilities of the database "for free". We develop andevaluate multiple data models for representing versioned data, as well as alight-weight partitioning scheme, LyreSplit, to further optimize the models forreduced query latencies. With LyreSplit, OrpheusDB is on average 1000x fasterin finding effective (and better) partitionings than competing approaches,while also reducing the latency of version retrieval by up to 20x relative toschemes without partitioning. LyreSplit can be applied in an online fashion asnew versions are added, alongside an intelligent migration scheme that reducesmigration time by 10x on average.

OrpheusDB: Bolt-on Versioning for Relational Databases