Data Replication Strategies for Fault Tolerance and Availability on Commodity Clusters

Recent work has shown the advantages of using persistent memory for transaction processing. In particular, the Vista transaction system uses recoverable memory to avoid disk I/O, thus improving performance by several orders of magnitude. In such a system, however, the data is safe when a node fails, but unavailable until it recovers, because the data is kept in only one memory. In contrast, our work uses data replication to provide both reliability and data availability while still maintaining very high transaction throughput. We investigate four possible designs for a primary-backup system, using a cluster of commodity servers connected by a write-through capable system area network (SAN). We show that logging approaches outperform mirroring approaches, even when communicating more data, because of their better locality. Finally, we show that the best logging approach also scales well to small shared-memory multiprocessors.