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SQLDoom Runs Original Doom’s Game Logic and Renderer in SQL

SQLDoom runs original Doom’s game logic and textured renderer in CedarDB. Its 5,900-line figure counts game-logic SQL, while Python handles input, timing and display.
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Yes: SQLDoom runs the original 1993 Doom game logic and textured renderer inside CedarDB. The headline’s 5,900 lines refer to SQL game logic, according to creator Lukas Vogel—not the entire project. A Python client still reads player input, advances the game clock and displays the frames returned by the database.

What “Doom in SQL” means

SQLDoom is not just a database query that prints a Doom-like scene. Its repository describes a port of the original game, including WAD map data, BSP traversal, textures, game logic and rendering. The core game state is updated in database tables, and a SQL query pipeline produces the framebuffer. The project repository and Vogel’s write-up document that division of work.

The client and database have distinct jobs:

  • SQL in CedarDB: game logic, state updates and rendering.
  • Python: reading input, driving the game clock and displaying the resulting bitmap.

So the project demonstrates that substantial game logic and rendering can be expressed in SQL; it does not mean that no code runs outside the database.

What the 5,900-line figure counts

Vogel says SQLDoom’s game logic is about 5,900 lines of SQL. He compares that with roughly 9,000 lines of the original Doom C source doing the same game-logic work. Those are the author’s figures for this comparison, not a general measure of how SQL and C implementations compare.

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The repository lists other substantial components: about 1,300 lines of Python for the WAD importer and about 1,300 lines of SQL for rendering, excluding comments, organized across 89 common table expressions (CTEs). The 5,900-line headline therefore should not be read as the total line count for every part of the project.

How the database runs a game

Game clock and state

The Python client triggers game tics at Doom’s original rate of 35 per second. Each tic advances the SQL-side game state. The client can request a rendered frame when needed; the game loop and frame rendering are decoupled rather than being one operation for every display refresh.

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Maps and rendering

A Python importer converts Doom WAD map data into database tables. Vogel describes the WAD format as relational in structure and reports that importing Doom 1 took about 18 seconds on his laptop. The renderer then uses SQL queries to process geometry and game state into a 320×200 framebuffer. The repository describes a textured renderer using BSP traversal, rather than the ASCII raycasting approach of the earlier DOOMQL experiment.

What performance has been reported

The project reports measurements from its author, not independent benchmark results. They depend on the hardware and scene:

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Measure Project-reported result
Game clock 35 tics per second, retaining Doom’s original clock rate.
Average tic with six awake monsters 2.15 ms, in the author’s measurements.
Tic in a described E4M1 scene with 46 awake monsters 10.45 ms, in the author’s measurements.
Rendering on the author’s Ryzen 7 PRO 7840U laptop Roughly 60 FPS, falling to 35 FPS in very busy scenes.

These figures describe reported tests on particular scenes and hardware; they are not performance guarantees for other machines or installations.

What you need to try SQLDoom

The published repository requires CedarDB Community Edition because SQLDoom uses CedarDB’s cedarscript functions. The README says a port to plpgsql may be possible, but does not claim the current code runs unchanged on PostgreSQL.

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  1. Set up CedarDB Community Edition and the Python dependencies psycopg2 and pygame, as described in the SQLDoom repository.
  2. Provide a Doom IWAD separately. The repository does not include WAD files; it says the shareware doom1.wad is sufficient for episode one, while retail WADs work if you own them.
  3. Follow the repository’s setup instructions to import the WAD and run the Python client against CedarDB.

SQLDoom’s code is licensed under GPL version 2 or later. That software license is separate from the terms governing Doom’s game data: the project does not bundle the WAD, and users need to obtain data they are entitled to use.

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SQLDoom versus DOOMQL

SQLDoom and DOOMQL are related experiments, but they are not the same implementation. DOOMQL, the earlier project identified by Vogel, is a multiplayer Doom-like game with raycasting and ASCII presentation. SQLDoom instead targets the original Doom’s game logic and textured BSP renderer. The DOOMQL repository documents that predecessor.

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Vogel’s reaction to the work was: “To be honest, I was surprised how easy it is to express pretty complicated game logic in SQL.” That is the author’s observation about this project, not a claim that SQL is generally the best tool for game development.

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