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There is no single Doom package with interchangeable PostgreSQL and SQLite back ends. The PostgreSQL example, pg_doom, is a C extension controlled through SQL and psql. SQLite examples range from DOOMQL, an original Doom-like game, to a Doom build running on Turso’s extended SQLite-derived virtual machine. A fourth project, SQLDoom, implements Doom in SQL but currently requires CedarDB, not vanilla PostgreSQL. Which one to choose depends on whether you want the original game, a database-native experiment, or the simplest route to a Doom-like demo.
How the four projects differ
| Project | Database or runtime | What runs through the database | Main qualification |
|---|---|---|---|
pg_doom |
PostgreSQL C extension | Doom core exposed through extension functions; a shell wrapper and psql handle interaction |
Requires a legally obtained WAD file |
| Turso VDBE Doom | Turso’s SQLite-derived virtual database engine (VDBE) | Compiled Doom bytecode runs in the database VM; a long-lived statement yields frames | Relies on Turso extensions beyond stock SQLite |
| DOOMQL | SQLite | An original Doom-like raycaster calculates simulation and framebuffer values | Its creators explicitly say it is not a Doom port |
| SQLDoom | CedarDB using the PostgreSQL wire protocol | Original Doom logic and rendering are implemented as SQL queries | Uses CedarScript functions and currently requires CedarDB |
These are separate projects, not competing configurations of one game. In particular, “runs with SQLite” can mean a purpose-built game whose calculations use SQLite, or compiled Doom running in Turso’s extended VM. Neither description should be generalized to stock SQLite without qualification.
How to run Doom in PostgreSQL with pg_doom
pg_doom is the direct PostgreSQL route if you want a Doom project integrated with a PostgreSQL server. It is a C extension—not ordinary SQL implementing the game. The extension provides an input procedure and a screen function; a wrapper sends input and reads output through psql. The project documentation is at the pg_doom repository.
Docker route
- Clone the
pg_doomrepository. - Place a legally obtained
doom.wadin the repository directory. The project does not include the game data. - Build the provided Dockerfile and run the resulting image interactively, following the repository’s current README commands.
- Use the documented controls: A, S, D, W, F, and E.
The Docker workflow is the repository’s convenient route. Its README describes the WAD as copyrighted and not freely distributable, so do not download it from an unofficial source. You need a lawful copy that you are entitled to use.
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Manual build route
The manual instructions target Debian-oriented Linux systems. They call for PostgreSQL development files, a C compiler, GNU Make, compiling and installing the extension, starting PostgreSQL, creating a database and extension, and running the input/output wrapper. The project says the procedure can be adapted to other Linux distributions; Windows preparation differs. Follow the repository’s current README for exact commands and platform details rather than assuming package names or setup steps are universal.
Treat any temporary server configuration as a local demonstration only. The README includes a broad trust-authentication example; do not expose a server using unrestricted trust access. Restrict network access and use appropriate credentials for any server that is reachable beyond your own machine. The project notes that refresh and input lag vary with the machine and player conditions.
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Can SQLite run Doom?
It depends what “Doom” and “SQLite” mean. DOOMQL uses SQLite for its own Doom-like game; Turso demonstrates the original Doom compiled to run in an extended SQLite-derived VM. These are different achievements, and only the latter describes running compiled Doom rather than a new raycaster.
DOOMQL: a Doom-like game built around SQLite
DOOMQL is an original raycaster, not a port of the 1993 Doom. SQLite performs simulation and framebuffer calculations; a Python terminal client writes the resulting bytes, and the terminal draws the final image. The project provides commands to play, inspect, reset, run a demo, benchmark, and verify the project. Its persistent play data is stored at .doomql/doomql.sqlite. This is the clearest option if the interesting part is using SQLite as the engine for a Doom-inspired experiment rather than playing the original game.
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Turso: compiled Doom in an extended SQLite-derived VM
Turso’s demonstration describes compiling Doom’s C code to LLVM IR and then to Turso’s VDBE bytecode. Game memory is represented by a BLOB in a database row, and a long-lived statement yields rendered frames through a result row. The sample can run in memory or persist state in a database file, with browser and native clients described.
This is not a capability of unmodified SQLite: the demonstration depends on Turso’s extensions to SQLite’s bytecode machinery. Choose it to explore that particular database VM experiment, not as a drop-in recipe for running Doom in any SQLite installation.
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SQLDoom: SQL game logic on CedarDB
CedarDB’s SQLDoom article describes the original Doom game logic and renderer implemented as SQL queries. Python is used for input, timing, and displaying the bitmap. CedarDB speaks the PostgreSQL wire protocol, but SQLDoom uses CedarScript functions and the article says it currently requires CedarDB. It is therefore a SQL implementation on a PostgreSQL-protocol database—not a documented setup for vanilla PostgreSQL.
The article lists CedarDB Community Edition, Python with psycopg2 and pygame, and a Doom IWAD as requirements. It identifies shareware doom1.wad as freely redistributable and sufficient for episode one; retail WADs work if you own them. Obtain game data only under terms that permit your use.
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How to choose a project
- Want a PostgreSQL extension tied to the original game? Start with
pg_doom, accounting for its build requirements and WAD dependency. - Want an SQLite-centered game experiment? Choose DOOMQL, understanding that it is Doom-like rather than the original Doom.
- Want compiled Doom running in a SQLite-derived VM? Explore Turso’s VDBE demonstration, which depends on Turso-specific extensions.
- Want to see original Doom logic expressed as SQL? SQLDoom is the relevant project, but its current CedarDB-specific functions rule out treating it as vanilla PostgreSQL.
Do the reported frame rates show which database is faster?
No. There is no controlled head-to-head PostgreSQL-versus-SQLite benchmark established by these project sources. The figures describe different implementations and conditions, so they cannot rank the databases.
- CedarDB author Lukas Vogel reports a 35 FPS game loop and rendering up to 60 Hz on his laptop for SQLDoom. These are author-reported figures for that implementation, not independent or cross-project results.
- Turso’s article reports over 60 fps after a specialized optimization in its VM demonstration. The author says performance records were not the project’s goal.
- DOOMQL provides a benchmark command, but that is not a result comparing it with the other projects.
Use those numbers as context for each author’s demonstration, not as evidence that one database engine is faster for Doom.
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