Minuet: A scalable distributed multiversion b-tree

Data management systems have traditionally been designed to sup-port either long-running analytics queries or short-lived transac-tions, but an increasing number of applications need both. For example, online games, socio-mobile apps, and e-commerce sites need to not only maintain operational state, but also analyze that data quickly to make predictions and recommendations that im-prove user experience. In this paper, we present Minuet, a dis-tributed, main-memory B-tree that supports both transactions and copy-on-write snapshots for in-situ analytics. Minuet uses main-memory storage to enable low-latency transactional operations as well as analytics queries without compromising transaction perfor-mance. In addition to supporting read-only analytics queries on snapshots, Minuet supports writable clones, so that users can cre-ate branching versions of the data. This feature can be quite useful, e.g. to support complex “what-if ” analysis or to facilitate wide-area replication. Our experiments show that Minuet outperforms a commercial main-memory database in many ways. It scales to hundreds of cores and TBs of memory, and can process hundreds of thousands of B-tree operations per second while executing long-running scans. 1