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.