Decibel: The Relational Dataset Branching System.
As scientific endeavors and data analysis become increasingly collaborative, there is a need for data management systems that natively support theversioningorbranchingof datasets to enable concurrent analysis, cleaning, integration, manipulation, or curation of data across teams of individuals. Common practice for sharing and collaborating on datasets involves creating or storing multiple copies of the dataset, one for each stage of analysis, with no provenance information tracking the relationships between these datasets. This results not only in wasted storage, but also makes it challenging to track and integrate modifications made by different users to the same dataset. In this paper, we introduce the Relational Dataset Branching System, Decibel, a new relational storage system with built-in version control designed to address these shortcomings. We present our initial design for Decibel and provide a thorough evaluation of three versioned storage engine designs that focus on efficient query processing with minimal storage overhead. We also develop an exhaustive benchmark to enable the rigorous testing of these and future versioned storage engine designs.
MIT CSAIL.
Michael
M
Maddox
MIT CSAIL.
David
D
Goehring
University of Chicago.
Aaron J
AJ
Elmore
MIT CSAIL.
Samuel
S
Madden
University of Illinois (UIUC).
Aditya
A
Parameswaran
University of Maryland (UMD).
Amol
A
Deshpande