Stronger semantics for low-latency geo-replicated storage

We present the first scalable, geo-replicated storage system that guarantees low latency, offers a rich data model, and provides “stronger” semantics. Namely, all client requests are satisfied in the local datacenter in which they arise; the system efficiently supports useful data model abstractions such as column families and counter columns; and clients can access data in a causally-consistent fashion with read-only and write-only transactional support, even for keys spread across many servers. The primary contributions of this work are enabling scalable causal consistency for the complex column-family data model, as well as novel, non-blocking algorithms for both read-only and write-only transactions. Our evaluation shows that our system, Eiger, achieves low latency (single-ms), has throughput competitive with eventually-consistent and non-transactional Cassandra (less than 7% overhead for one of Facebook's real-world workloads), and scales out to large clusters almost linearly (averaging 96% increases up to 128 server clusters).