# StealthDB: a Scalable Encrypted Database with Full SQL Query Support

arXiv: https://arxiv.org/abs/1711.02279 · HTML: https://mlsanity.com/paper/1711.02279/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Nov 2017.

## Built on by (most cited first, 2 of 2)

- [A Survey of Secure Computation Using Trusted Execution Environments](https://mlsanity.com/paper/2302.12150/) (2023)
- [When Agents Handle Secrets: A Survey of Confidential Computing for Agentic AI](https://mlsanity.com/paper/2605.03213/) (2026)

## Abstract (arXiv)

Encrypted database systems provide a great method for protecting sensitive data in untrusted infrastructures. These systems are built using either special-purpose cryptographic algorithms that support operations over encrypted data, or by leveraging trusted computing co-processors. Strong cryptographic algorithms (e.g., public-key encryptions, garbled circuits) usually result in high performance overheads, while weaker algorithms (e.g., order-preserving encryption) result in large leakage profiles. On the other hand, some encrypted database systems (e.g., Cipherbase, TrustedDB) leverage non-standard trusted computing devices, and are designed to work around the architectural limitations of the specific devices used. In this work we build StealthDB - an encrypted database system from Intel SGX. Our system can run on any newer generation Intel CPU. StealthDB has a very small trusted computing base, scales to large transactional workloads, requires minor DBMS changes, and provides a relatively strong security guarantees at steady state and during query execution. Our prototype on top of Postgres supports the full TPC-C benchmark with a 30% decrease in the average throughput over an unmodified version of Postgres operating on a 2GB unencrypted dataset.