VeriBench: Analyzing the Performance of Database Systems with Verifiability
Cong Yue, Meihui Zhang, Changhao Zhu, Gang Chen, Dumitrel Loghin, Beng Chin Ooi
Abstract
Database systems are paying more attention to data security in recent years. Immutable systems such as blockchains, verifiable databases, and ledger databases are equipped with various verifiability mechanisms to protect data. Such systems often adopt different threat models, and techniques, therefore, have different performance implications compared to traditional database systems. So far, there is no uniform benchmarking tool for evaluating the performance of these systems, especially at the level of verification functions. In this paper, we first survey the design space of the verifiability-enabled database systems along five dimensions: threat model, authenticated data structure (ADS), query processing, verification, and auditing. Based on this survey, we design and implement VeriBench, a benchmark framework for verifiability-enabled database systems. VeriBench enables a fair comparison of systems designed with different underlying technologies that share the client-side verification scheme, and focuses on design space exploration to provide a deeper understanding of different system design choices. VeriBench incorporates micro- and macro-benchmarks to provide a comprehensive evaluation. Further, VeriBench is designed to enable easy extension for benchmarking new systems and workloads. We run VeriBench to conduct a comprehensive analysis of state-of-the-art systems comprising blockchains, ledger databases, and log transparency technologies. The results expose the weaknesses and strengths of each underlying design choice, and the insights should serve as guidance for future development.
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