Fault-Tolerant Partial Replication in Large-Scale Database Systems

TL;DR

This paper presents a decentralized protocol for transaction commitment in large-scale, partially replicated databases that enhances scalability and performance by only ordering conflicting transactions and applying updates directly.

Contribution

It introduces a novel algorithm that ensures serializability and fault tolerance while allowing transactions to execute faster and commit in smaller committees.

Findings

Transactions execute faster with the new protocol.

The system maintains serializability and fault tolerance.

Scalability improves as the number of databases and transactions increases.

Abstract

We investigate a decentralised approach to committing transactions in a replicated database, under partial replication. Previous protocols either re-execute transactions entirely and/or compute a total order of transactions. In contrast, ours applies update values, and orders only conflicting transactions. It results that transactions execute faster, and distributed databases commit in small committees. Both effects contribute to preserve scalability as the number of databases and transactions increase. Our algorithm ensures serializability, and is live and safe in spite of faults.