Evaluating the Price of Consistency in Distributed File Storage Services

Distributed file storage services (DFSS) such as Dropbox, iCloud, SkyDrive, or Google Drive, offer a filesystem interface to a distributed data store. DFSS usually differ in the consistency level they provide for concurrent accesses: a client might access a cached version of a file, see the immediate results of all prior operations, or temporarily observe an inconsistent state. The selection of a consistency level has a strong impact on performance. It is the result of an inherent tradeoff between three properties: consistency, availability, and partition-tolerance. Isolating and identifying the exact impact on performance is a difficult task, because DFSS are complex designs with multiple components and dependencies. Furthermore, each system has a different range of features, its own design and implementation, and various optimizations that do not allow for a fair comparison. In this paper, we make a step towards a principled comparison of DFSS components, focusing on the evaluation of consistency mechanisms. We propose a novel modular DFSS testbed named FlexiFS, which implements a range of state-of-the-art techniques for the distribution, replication, routing, and indexing of data. Using FlexiFS, we survey six consistency levels: linearizability, sequential consistency, and eventual consistency, each operating with and without close-to-open semantics. Our evaluation shows that: (i) as expected, POSIX semantics (i.e., linearizability without close-to-open semantics) harm performance; and (ii) when close-to-open semantics is in use, linearizability delivers performance similar to sequential or eventual consistency.