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Replication is a key mechanism to achieve scalability and fault-tolerance in databases. Its importance has recently been further increased because of the role it plays in achieving elasticity at the database layer. In database replication, the biggest challenge lies in the trade-off between performance and consistency. A decade ago, performance could only be achieved through lazy replication at the expense of transactional guarantees. The strong consistency of eager approaches came with a high cost in terms of reduced performance and limited scalability. Postgres-R combined results from distributed systems and databases to develop a replication solution that provided both scalability and strong consistency. The use of group communication primitives with strong ordering and delivery guarantees together with optimized transaction handling (tailored locking, transferring logs instead of re-executing updates, keeping the message overhead per transaction constant) were a drastic departure from the state-of-the-art at the time. Ten years later, these techniques are widely used in a variety of contexts but particularly in cloud computing scenarios. In this paper we review the original motivation for Postgres-R and discuss how the ideas behind the design have evolved over the years.