Project ideas from Hacker News discussions.

We ported the original Doom to SQL

📝 Discussion Summary (Click to expand)

Theme 1 – SQL as a surprisingly expressive language for complex logic
Many commenters marveled at how much functionality can be squeezed into SQL, noting that the game’s logic fits in fewer lines than the original C implementation.
- “The game logic is just ~5900 lines of SQL. While this sounds a lot, it’s definitely less than the original C source code which does the same in about 9000 lines!” — paul‑vernon
- “Yes, this is fantastic! I'm trying it right now…. This works way better than I would have expected, since, well, it's sql all the way down.” — Alive‑in‑2025

Theme 2 – Trade‑offs, concurrency pitfalls, and the “malpractice” debate
While the approach is clever, several users warned about atomicity, deadlocks, and scaling nightmares when using SQL tables as mutable game state.
- “Less lines of code than vanilla C while abusing query planning as a state machine is peak engineering malpractice. I love it.” — soltanov
- “With multiple players you can imagine that there would sometimes be issues. Some of the deadlock problems early on were horrific; scaling was a nightmare. But everything was atomic.” — noduerme

Theme 3 – Real‑world applicability and operational observations
Beyond the novelty, participants pointed out practical benefits: multi‑region servers, ease of testing via DB replication, and the use of stored procedures for business‑logic‑heavy domains.
- “I want to point out that they set up an EU and US multiplayer server! Nice touch.” — ralfd
- “When I was working in semiconductor manufacturing, we relied very heavily on stored procedures and SQL to operate the factory… Testing this stuff was trivial because we replicated the prod DB every morning…” — bob1029


🚀 Project Ideas

Generating project ideas…

Relang: Expressive Relational Language Compiling to SQL

Summary

  • Provides a high‑level relational language that transpiles to efficient SQL/plpgsql, letting developers express complex game or business logic in far fewer lines than raw SQL.
  • Eliminates the impedance mismatch between procedural code and the database while preserving ACID guarantees and set‑based performance.

Details

Key Value
Target Audience Developers building complex domain logic (games, fintech, SaaS) who want to keep code inside the DB
Core Feature Language with pattern matching, recursion, and modular compiles to optimized SQL/plpgsql functions
Tech Stack Rust compiler, LLVM backend, PostgreSQL extension (pgx), CI/CD for testing
Difficulty Medium
Monetization Revenue-ready: Hosted compiler + DB service (subscription tiers)

Notes

  • HN comment bob1029: “We relied very heavily on stored procedures and SQL to operate the factory… want literally one system the business operates inside of.”
  • HN comment paul‑vernon: “Makes me wonder how good a better relational language than SQL might be for general programming.”

CheckpointJS: Fault‑Tolerant Incremental Computation Engine

Summary

  • Persists intermediate results of long‑running computational jobs to PostgreSQL, enabling automatic resumption after hardware failure without recomputing from scratch.
  • Gives data engineers a simple DAG‑based API to define checkpoints and get exactly‑once semantics.

Details

Key Value
Target Audience Data engineers and scientists running lengthy ETL, ML training, or batch jobs
Core Feature Automatic checkpoint storage in Postgres tables with resume‑from‑failure semantics
Tech Stack Python (or Node.js) SDK, PostgreSQL, optional Rust worker for high‑throughput stages, Docker orchestration
Difficulty Medium
Monetization Hobby (open‑source) – optional hosted SaaS with per‑job pricing

Notes

  • HN comment worldsavior: “how to counter hardware failure without needing to calculate everything from the start?”
  • HN comment noduerme: “Atomicity guarantees at least that there is a consistent state that won’t get lost… scaling was a nightmare.”

PostgresHTAP: One‑Click Self‑Hostable HTAP Stack

Summary

  • Bundles PostgreSQL with a columnar store and automatic query routing to deliver HTAP performance comparable to TiDB/TiFlash using familiar Postgres syntax.
  • One‑click Docker‑Compose setup lets teams run analytical queries on live operational data without a separate ETL pipeline.

Details

Key Value
Target Audience Companies seeking a Postgres‑compatible alternative to TiDB/TiFlash for mixed OLTP/OLAP workloads
Core Feature Transparent routing of OLTP queries to row store and OLAP queries to columnar store with live replication
Tech Stack PostgreSQL, Citus/pg_columnar (or DuckDB FDW), Docker‑Compose, Prometheus/Grafana for monitoring
Difficulty High
Monetization Revenue-ready: Enterprise support license or managed offering (per‑node pricing)

Notes

  • HN comment vovavili: “I was actually just recently looking if there is a self-hostable alternative to a HTAP system like TiDB + TiFlash with a Postgres-compatible syntax…”
  • HN comment bob1029 (again): “When people advocate for spending big piles of money with Microsoft, Oracle and IBM, they are generally going for something like the above. They want literally one system the business operates inside of.”

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