O rpheus DB

Abstract

Data science teams often collaboratively analyze datasets, generating dataset versions at each stage of iterative exploration and analysis. There is a pressing need for a system that can support dataset versioning, enabling such teams to efficiently store, track, and query across dataset versions. We introduce O rpheus DB, a dataset version control system that " bolts on " versioning capabilities to a traditional relational database system, thereby gaining the analytics capabilities of the database "for free". We develop and evaluate multiple data models for representing versioned data, as well as a light-weight partitioning scheme, L yre S plit , to further optimize the models for reduced query latencies. With L yre S plit , O rpheus DB is on average 10 3 × faster in finding effective (and better) partitionings than competing approaches, while also reducing the latency of version retrieval by up to 20× relative to schemes without partitioning. L yre S plit can be applied in an online fashion as new versions are added, alongside an intelligent migration scheme that reduces migration time by 10× on average.