Checking Causal Consistency of Distributed Databases

TL;DR

This paper introduces a tool that automatically verifies whether distributed database executions adhere to causal consistency by translating the problem into Datalog query solving, enabling efficient testing of real systems.

Contribution

It presents a novel reduction of causal consistency checking to Datalog query solving, with an implementation and experimental validation on real distributed databases.

Findings

The approach efficiently detects causal consistency violations.

The tool successfully applied to real case studies.

Reduction to Datalog queries simplifies the verification process.

Abstract

The CAP Theorem shows that (strong) Consistency, Availability, and Partition tolerance are impossible to be ensured together. Causal consistency is one of the weak consistency models that can be implemented to ensure availability and partition tolerance in distributed systems. In this work, we propose a tool to check automatically the conformance of distributed/concurrent systems executions to causal consistency models. Our approach consists in reducing the problem of checking if an execution is causally consistent to solving Datalog queries. The reduction is based on complete characterizations of the executions violating causal consistency in terms of the existence of cycles in suitably defined relations between the operations occurring in these executions. We have implemented the reduction in a testing tool for distributed databases, and carried out several experiments on real case studies, showing the efficiency of the suggested approach.