The CAP theorem is a fundamental result that applies to distributed storage
systems. In this paper, we first present and prove two CAP-like impossibility
theorems. To state these theorems, we present probabilistic models to
characterize the three important elements of the CAP theorem: consistency (C),
availability or latency (A), and partition tolerance (P). The theorems show the
un-achievable envelope, i.e., which combinations of the parameters of the three
models make them impossible to achieve together. Next, we present the design of
a class of systems called PCAP that perform close to the envelope described by
our theorems. In addition, these systems allow applications running on a single
data-center to specify either a latency SLA or a consistency SLA. The PCAP
systems automatically adapt, in real-time and under changing network
conditions, to meet the SLA while optimizing the other C/A metric. We
incorporate PCAP into two popular key-value stores -- Apache Cassandra and
Riak. Our experiments with these two deployments, under realistic workloads,
reveal that the PCAP system satisfactorily meets SLAs, and performs close to
the achievable envelope. We also extend PCAP from a single data-center to
multiple geo-distributed data-centers