django-async-orm VS aiosql

Compare django-async-orm vs aiosql and see what are their differences.


Bringing Async Capabilities to django ORM (by rednaks)


Simple SQL in Python (by nackjicholson)
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django-async-orm aiosql
6 9
126 1,202
- -
0.0 8.8
3 months ago 17 days ago
Python Python
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.


Posts with mentions or reviews of django-async-orm. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-07.


Posts with mentions or reviews of aiosql. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-16.
  • Project template without ORM
    3 projects | /r/FastAPI | 16 Jan 2023
    I prefer to use aiosql to organize my SQL and have it in a SQL folder. It looks like this where colons specify variables:
  • If you could choose any Python web framework to build APIs for a startup, which one would you choose and why?
    4 projects | /r/Python | 1 Oct 2022
    I tend to do a lot of data-heavy projects, so I tend to eschew ORM-style code and use a project called aiosql to bind raw SQL to python methods, and offload as much expensive computation to the DB as possible. If I'm prototyping an endpoint (e.g. calculating percentiles for some midsized time-series data), and just need a non-performant working placeholder, it's extremely easy to dump a SQL table to pandas and yeet something together in a few lines - then smoothly replace it with a more performant SQL query down the road. Highly contextual move, but I find it to be an awesome balancing point between flexibility, scalability, performance, productivity, etc.
  • Which not so well known Python packages do you like to use on a regular basis and why?
    25 projects | /r/Python | 26 Aug 2022
    As one of the rare Python developers who actually like SQL, my favourite database library is aiosql
  • The Data-Oriented Design Process for Game Development
    3 projects | | 27 May 2022
    I've been doing something in this vein for a big personal project, using this python library:

    In short, I'm using a run of the mill stack (Caddy/Gunicorn/Flask/Postgres) - but with the twist that all my core logic is defined in plaintext SQL files, which get bound into namespaced Python methods by aiosql. Routing, error handling, templating, etc. are all done in Python - but all data manipulation and processing are outsourced to the DB level. All database object definitions are laid out in a massive, idempotent "init_db" method that gets called at launch, so I can essentially point the app at a fresh instance of Postgres and rebuild from scratch. The design is primarily driven by my personal distaste for ORMs, but I've found it extremely beneficial in terms of rigid typing, integrity checks, and performance.

  • Is it bad practice for my flask API to run raw SQL queries against my DB to get/post data?
    2 projects | /r/Python | 25 Jan 2022
    Definitely check out if you want to stick with SQL
    2 projects | /r/Python | 25 Jan 2022
    Have a look at this library: It lets you keep your SQL queries in separate files and handles all of the parameterising for you.
  • Django 4.0 release candidate 1 released
    11 projects | | 22 Nov 2021
    I took that approach on my latest Flask project and it’s gone quite swimmingly. The problem I ran into was that a lot of the ecosystem, and therefore documentation, blog posts, helper libraries, etc., are all written under the assumption that you’re using an ORM. It took a while to figure out how to work around that, but once I did, I was home clear.

    I also used a helper library to automatically map namespaced .sql files onto python functions with various return types, which made the development process way more elegant: Absolute game changer if you plan to go this route - can’t recommend it highly enough.

  • FastAPI framework, high perf, easy to learn, fast to code, ready for production
    15 projects | | 1 Feb 2021
    I've been using FastAPI for some time, and now I'm using it as a full web framework (not just for REST APIs). I like writing SQL without ORMs, so the combination of aiosql[0] + FastAPI + Jinja2 works great. Add HTMX[1] and even interactive websites become easy.

    That's in fact the stack I am using to build and I couldn't enjoy it more.

    Thanks Sebastián for creating it!


What are some alternatives?

When comparing django-async-orm and aiosql you can also consider the following projects:

tortoise-orm - Familiar asyncio ORM for python, built with relations in mind

fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production

databases - Async database support for Python. 🗄

full-stack-fastapi-postgresql - Full stack, modern web application generator. Using FastAPI, PostgreSQL as database, Docker, automatic HTTPS and more.

django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs

Django - The Web framework for perfectionists with deadlines.

docker-django-example - A production ready example Django app that's using Docker and Docker Compose.

celery - Distributed Task Queue (development branch)

cookiecutter-django - Cookiecutter Django is a framework for jumpstarting production-ready Django projects quickly.

fastapi-crudrouter - A dynamic FastAPI router that automatically creates CRUD routes for your models

Pebble - Java Template Engine

mangum - AWS Lambda support for ASGI applications