BASIC: An alternative to BASE for large-scale data management system

Big data applications demand and consequently lead to developments of large-scale data management systems, which provide high scalability by partitioning data across multiple servers. Since conventional transactional access is quite expensive, many real world large-scale distributed systems eschew transactional functionality and adopt semantics of atomic multi-partition operations. Accordingly, BASE, a consistency model weaker than ACID, is commonly used to guarantee availability. In this work, we identify a new consistency model-BASIC (Basic Availability, Scalability, Instant Consistency) that matches the requirements where extra efforts are not needed to manipulate inconsistent soft states. We present a timestamp-based formula protocol for BASIC that can enforce Instant Consistency while achieving linear scalability (via logical formula caching, dynamic timestamp ordering) and achieve Basic Availability in the presence of partial failure and network partition (via partition independence, genuine atomic commit). Our extensive experimental results verify the scalability of BASIC and demonstrate that the limited overhead induced by BASIC pays a reasonable price for keeping all soft states consistent.