  Consistency in data storage systems requires any read operation to return the
most recent written version of the content. In replicated storage systems,
consistency comes at the price of delay due to large-scale write and read
operations. Many applications with low latency requirements tolerate data
staleness in order to provide high availability and low operation latency.
Using age of information as the staleness metric, we examine a data updating
system in which real-time content updates are replicated and stored in a
Dynamo-style quorum- based distributed system. A source sends updates to all
the nodes in the system and waits for acknowledgements from the earliest subset
of nodes, known as a write quorum. An interested client fetches the update from
another set of nodes, defined as a read quorum. We analyze the staleness-delay
tradeoff in replicated storage by varying the write quorum size. With a larger
write quorum, an instantaneous read is more likely to get the latest update
written by the source. However, the age of the content written to the system is
more likely to become stale as the write quorum size increases. For shifted
exponential distributed write delay, we derive the age optimized write quorum
size that balances the likelihood of reading the latest update and the
freshness of the latest update written by the source.
