You can run Doom’s game logic, state, and renderer inside a SQL database with CedarDB’s SQLDoom project. In its documented setup, Python handles keyboard input, advances the game clock, and displays frames; the database does the game work. Despite the title’s WebAssembly reference, SQLDoom is not Doom compiled to WebAssembly. This guide explains the CedarDB route and distinguishes it from browser-based DuckDB-WASM and a conventional Doom WASM module.
What “Doom in a SQL database” means
SQLDoom is an implementation of Doom’s game logic and rendering in database queries and functions. CedarDB describes the aim as rendering an image like Doom while keeping the game loop and rendering SQL-based. Its documented Python client uses pygame to collect input and show the returned bitmap, and advances game tics 35 times per second. The database stores game state and produces the rendered frame. See CedarDB’s technical article and the SQLDoom repository.
That division of work matters: a client still participates, but it is not running Doom’s game engine. CedarDB’s technical article describes a complete 320×200 framebuffer and rendering at up to 60 Hz on the author’s laptop. That reported display rate is distinct from the 35-Hz game-tic schedule in the repository; neither figure is a general performance guarantee.
Choose the implementation that matches your goal
| Project | Where the game runs | What the host or client does | Important distinction |
|---|---|---|---|
| SQLDoom | Game logic, state, and renderer run in SQL inside CedarDB. | Python handles input, timing, and frame display. | Uses CedarDB-specific cedarscript functions in its documented form; PostgreSQL wire-protocol compatibility does not make it a drop-in PostgreSQL app. Project repository |
| DuckDB-DOOM | SQL queries run in DuckDB-WASM in a browser. | HTML and JavaScript provide the interface. | An experimental Doom-like raycasting project with ASCII rendering, not the same SQLDoom implementation. Project repository |
| doom.wasm | Doom itself is compiled as a WebAssembly module. | A host runtime implements imports, instantiates the module, calls initialization and tick functions, forwards key events, and renders. | WebAssembly is the game module here; game logic is not thereby SQL-based. Project repository |
| pg_doom | Doom core is integrated through a PostgreSQL C extension. | A shell wrapper sends SQL input calls and displays screen-function output. | A separate route requiring an extension build/install and a Doom WAD. Project repository |
If your goal is specifically to put game logic and rendering in database SQL, follow SQLDoom. If you only want Doom running through WebAssembly in a browser or host runtime, a WASM-module project is architecturally different and may fit better.
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What you need for the SQLDoom setup
- CedarDB Community Edition: The repository’s documented implementation requires CedarDB because some functions use cedarscript. It notes that porting those functions to plpgsql may be possible, but does not document a ready-to-run PostgreSQL version.
- Python dependencies: Python with
psycopg2andpygame, as listed by the repository. - Doom game data: An IWAD. The repository says the shareware
doom1.wadis freely redistributable and sufficient for episode 1. Retail WADs work if you own them; retail game data is not bundled or represented as freely redistributable.
Check the repository’s current instructions for the exact dependencies and CedarDB launch method, since project requirements can change.
Load the game data and launch SQLDoom
- Start a CedarDB instance. Use the current CedarDB Community Edition instructions and make sure it is reachable with the credentials and database name you plan to use.
- Import an episode from the directory containing your WAD:
python3 wad_loader.py doom1.wad --dsn "postgresql://postgres:secret@localhost:5432/postgres"
Replace the example connection credentials and database settings with your own. The repository estimates an episode import at about 18 seconds; actual time can vary by environment. - Start the Python client:
DB_DSN="dbname=postgres user=postgres host=localhost port=5432" python3 doom_client.py
The client connects to the database, collects input, drives game tics, and displays the frames returned by SQLDoom.
These commands and filenames follow the project’s documented setup; consult the repository if its file layout or launch instructions have changed.
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How the game loop and performance are reported
The SQLDoom repository schedules a game tic every 1/35 second. It reports an average tic time of 2.15 ms with six monsters awake, and a worst case of 10.45 ms on E4M1 with 46 monsters awake. These are project-reported measurements, not independent benchmarks, and should not be generalized to other hardware or workloads.
The same repository describes the SQL tic logic as about 5,900 lines, compared with 9,000 lines in the original Doom. That is a project-reported code-size comparison, not a measure of speed or feature equivalence. CedarDB’s article separately reports 320×200 rendering at up to 60 Hz on the author’s laptop; rendering rate and game-tic rate describe different parts of the system.
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Optional: run the documented multiplayer setup
The project also documents a deathmatch route using player roles, a referee script, and a browser client. The referee owns the shared 35-Hz clock; the project says it supports up to four players. Database transaction atomicity and access controls are used to provide consistent views of game state and constrain client API access.
- Create the player roles using the SQLDoom instructions.
- Start
doom_server.pywith the documented environment settings. - Serve the browser client through
doom_web.pyand connect the players using the project’s documented flow.
The repository’s multiplayer setup is project-specific; follow its current instructions for role creation, environment variables, and client connection details: SQLDoom repository.
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