In this paper, we look back at the evolution of Yahoo!'s geo-replicated cloud data store from a research project called PNUTS to a globally deployed production system called Sherpa, share some of the lessons learned along the way, and finally, compare PNUTS with current operational cloud stores.

We describe PNUTS, a massively parallel and geographically distributed database system for Yahoo!'s web applications. PNUTS provides data storage organized as hashed or ordered tables, low latency for large numbers of concurrent requests including updates and queries, and novel per-record consistency guarantees. It is a hosted, centrally managed, and geographically distributed service, and utilizes automated load-balancing and failover to reduce operational complexity. The first version of the system is currently serving in production. We describe the motivation for PNUTS and the design and implementation of its table storage and replication layers, and then present experimental results.