Pick Django when you are building a full application with a relational data model, user accounts, an admin back office and server-rendered pages or a large REST API, and you want proven defaults for all of it. Pick FastAPI when you are building API-only services, especially async, I/O-heavy ones such as model-serving endpoints, LLM gateways and microservices, and you want typed request validation and OpenAPI docs generated from your code. Many teams use both: Django for the core product and admin, FastAPI for focused AI and integration services.
Django gives you a whole application architecture: models define your schema, migrations evolve it, the admin gives operations teams a usable back office on day one, and the auth system handles users, groups, permissions and sessions. Recent releases keep adding built-in features. Django 6.0 added Content Security Policy support, template partials and a built-in Tasks framework for running work outside the request cycle. The cost is that you work Django's way, and parts of the stack (ORM, middleware, many third-party apps) are still primarily synchronous.
FastAPI gives you a fast, typed way to define HTTP endpoints. You declare request and response shapes with Python type hints and Pydantic models; FastAPI validates input, serializes output and publishes an OpenAPI schema with interactive docs. Dependency injection handles auth, database sessions and shared resources. Everything else, including the ORM, migrations, admin and background jobs, is your choice. That makes FastAPI excellent for focused services and more work for full products.
FastAPI is usually faster for I/O-bound APIs because it runs on ASGI with an async event loop, so one worker can hold many concurrent requests that are waiting on databases, other services or LLM APIs. Django can also run async views on ASGI, and its ORM has async methods, but many Django apps and plugins remain sync, which limits the gains in practice.
For CPU-bound work, neither framework matters much: Python's interpreter is the limit, and you scale with more processes or move heavy work to background workers. For typical CRUD applications backed by Postgres, a well-indexed Django app and a well-written FastAPI app both spend most of their time in the database. Common performance fixes are the same: avoid N+1 queries (select_related and prefetch_related in Django, eager loading in SQLAlchemy), pool connections, cache hot reads and keep slow work out of request handlers.
One FastAPI-specific trap: calling blocking code (a sync database driver, requests, heavy CPU work) inside an async def endpoint blocks the event loop and hurts every concurrent request. Use async drivers, define the endpoint with plain def so it runs in the threadpool, or offload the work.
Download numbers show FastAPI's reach in services: pypistats recorded about 382 million FastAPI downloads in the last month versus about 41 million for Django, as of October 30, 2026. Downloads mostly reflect CI and container builds, not developers, so treat this as a signal of how often FastAPI is installed in pipelines. The 2025 Stack Overflow Developer Survey put usage closer: 14.8% of respondents used FastAPI and 12.6% used Django.
Django publishes a clear support schedule: 5.2 LTS receives security fixes until April 2028, 6.0 until April 2027 and 6.1 until December 2027, with 6.2 LTS planned for April 2027. Django has also announced that from its 2028 release onward every feature release will get the same three-year support period. FastAPI is still on 0.x versions and releases frequently; pin versions, read release notes and run tests on upgrades, because minor versions occasionally change behavior.
Both frameworks draw from the large Python talent pool. Django experience is common among product and full-stack engineers who have built SaaS apps, marketplaces and internal tools. FastAPI experience is common among backend and ML engineers who build services and model APIs. The senior signals differ: for Django, ORM performance, migrations on large tables, permissions design and upgrade experience; for FastAPI, async correctness, dependency injection design, Pydantic modeling and SQLAlchemy session handling. Use our Python interview questions and see pay bands on our Python developer rates page.
Both are free and open source. Django usually costs less to build a full product with, because you are not assembling auth, admin and migrations yourself. FastAPI can cost less to run for high-concurrency I/O workloads, because async workers hold more requests per process. For most teams, the bigger cost driver is how much glue code you write and maintain, which favors Django for products and FastAPI for narrow services.
Ryz Labs Python engineers work on your team on US business hours, with same-day code review, and most ship code in their first week. Only the top 1% of the tens of thousands of engineers we interview make it. You can hire Django developers or Python developers with FastAPI experience, or bring in a team through our Python development services. When the FastAPI service fronts an LLM or retrieval system, our AI pod teams build that system in your cloud and repos alongside your engineers.
Typical cost is $7,000 to $15,000 per engineer per month by seniority, and leads are quoted per team. If you need a trial gig or hourly freelance work before talking to anyone, a self-serve marketplace fits better than we do.
For I/O-bound APIs with many concurrent requests, FastAPI is usually faster because it is async-native on ASGI. For database-heavy CRUD apps, both spend most of their time in the database, so query design matters more than the framework.
For API-only services, yes. For full products, replacing Django means rebuilding the ORM layer, migrations, admin and auth from separate libraries. Most teams keep Django for the core product and use FastAPI for focused services.
FastAPI is the more common choice for model serving, LLM gateways and retrieval APIs because of async I/O, Pydantic validation and automatic OpenAPI docs. Django works well when the AI feature lives inside a larger product with users and an admin.
Yes. Django supports async views and async ORM methods when run on ASGI. Many third-party Django apps and parts of the stack are still synchronous, so the practical gains depend on your dependencies.
For maximum stability, Django 5.2 LTS, supported until April 2028. For the newest features, such as built-in background tasks and CSP support, Django 6.0 or 6.1. Django 6.2 LTS is planned for April 2027.
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