OrpheusDB: Bolt-on Versioning for Relational Databases
- Silu Huang ,
- Liqi Xu ,
- Jialin Liu ,
- Aaron J. Elmore ,
- Aditya G. Parameswaran
43th International Conference on Very Large Data Bases (VLDB) |
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 ORPHEUSDB, 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, LYRESPLIT, to further optimize the models for reduced query latencies. With LYRESPLIT, ORPHEUSDB is on average 103× 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. LYRESPLIT 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.