VeriBench: Analyzing the Performance of Database Systems with Verifiability

Cong Yue, Meihui Zhang, Changhao Zhu, Gang Chen, Dumitrel Loghin, Beng Chin Ooi

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)

Abstract

Database systems are paying more attention to data security inrecent years. Immutable systems such as block chains, 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 Veri Bench, 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. Veri Bench incorporates micro- and macro-bench marks to provide a comprehensive evaluation. Further, Veri Bench is designed to enable easy extension for benchmarking new systems and workloads. We run Veri Bench to conduct a comprehensive analysis of state-of-the-art systems comprising block chains, 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.

Original languageEnglish
Pages (from-to)2145-2157
Number of pages13
JournalProceedings of the VLDB Endowment
Volume16
Issue number9
DOIs
Publication statusPublished - 2023
Event49th International Conference on Very Large Data Bases, VLDB 2023 - Vancouver, Canada
Duration: 28 Aug 20231 Sept 2023

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