Postgres rewritten in Rust, now passing 100% of the Postgres regression tests

AI vs. “Real” Rewrites

• Many want a clear distinction between AI-driven rewrites and human rewrites; others argue quality and verification matter more than authorship.
• Some see “rewrite in Rust using LLMs” as a meme or vibe project, often done fast by a single person with no long‑term maintenance plan.
• Others view this as an important proof-of-concept showing how cheap large-scale language ports have become, potentially enabling modernization (e.g., COBOL-era systems).

Tests, Reliability, and “Production Scars”

• Passing 100% of Postgres’ regression tests is considered impressive, but many stress that this only proves absence of known regressions.
• Repeated concerns:
  • Real reliability comes from years of production incidents and “scar tissue,” not just tests.
  • Tests don’t cover every success path, concurrency edge case, or performance corner.
  • Overfitting to tests is possible, especially for LLMs.
• Some suggest differential testing (run both DBs and compare outputs), property-based testing, fuzzing, Jepsen-style tests, and mining bug reports into new tests.

Rust, Memory Safety, and Performance

• Supporters: Rust’s safety model and a thread‑per‑connection architecture could simplify internals, reduce shared-memory complexity, and unlock better parallelism.
• Critics: There are thousands of unsafe usages (parser especially), so many C-style risks remain; some ask “why Rust at all” if it’s this unsafe.
• Project author claims:
  • Current published version is ~8× slower than Postgres.
  • A new, unreleased version is ~50% faster on transactional workloads and ~300× faster on analytic workloads, with columnar storage and batch execution, ~2× slower than ClickHouse on clickbench.

Licensing and Legality

• The port is AGPL; some dislike moving from a permissive Postgres license to copyleft.
• Debate whether LLM‑generated translations are derivative works, new works, or even copyrightable at all; consensus in thread is “legally murky,” but permissive upstream likely allows more restrictive wrapping.

Maintenance, Trust, and Use in Production

• Many see this as an interesting experiment or learning tool, not something to run in production “for years” yet.
• Concerns about:
  • Single‑author bus factor.
  • Reviewability of thousands of AI‑generated commits.
  • Long‑term community, extension ecosystem, and backwards‑compatible upgrades.
• Some propose a positive use: run such rewrites against real workloads to discover missing tests and feed improvements back to upstream Postgres.