Benchmarking Analytical Query Processing in Intel SGXv2
Abstract
Trusted Execution Environments (TEEs), such as Intel's Software Guard Extensions (SGX), are increasingly being adopted to address trust and compliance issues in the public cloud. Intel SGX's second generation (SGXv2) addresses many limitations of its predecessor (SGXv1), offering the potential for secure and efficient analytical cloud DBMSs. We assess this potential and conduct the first in-depth evaluation study of analytical query processing algorithms inside SGXv2. Our study reveals that, unlike SGXv1, state-of-the-art algorithms like radix joins and SIMD-based scans are a good starting point for achieving high-performance query processing inside SGXv2. However, subtle hardware and software differences still influence code execution inside SGX enclaves and cause substantial overheads. We investigate these differences and propose new optimizations to bring the performance inside enclaves on par with native code execution outside enclaves.
Cite
@article{arxiv.2403.11874,
title = {Benchmarking Analytical Query Processing in Intel SGXv2},
author = {Adrian Lutsch and Muhammad El-Hindi and Matthias Heinrich and Daniel Ritter and Zsolt István and Carsten Binnig},
journal= {arXiv preprint arXiv:2403.11874},
year = {2025}
}
Comments
13 pages, 17 figures; To be published in EDBT 2025; Code available at: https://github.com/DataManagementLab/sgxv2-analytical-query-processing-benchmarks; major changes: overhauled figures, improved section 4.2, added new section 7, improved experiments, conference template