FastAPI vs Django

Django is a framework for building a whole web application. On the first day you have an ORM, migrations, user accounts, permissions, sessions, forms, and an admin panel your operations team can use. That is a lot of product you do not have to write, and it is why Django has stayed a sensible default for twenty years.

FastAPI is a framework for building an API. On the first day you have routing, request validation through Pydantic, dependency injection, and interactive OpenAPI docs generated from your type hints. Everything else, the database layer, migrations, auth, and any admin, is a choice you make. For a team that knows what it wants, that is speed. For a team that does not, it is a pile of decisions that Django would have made for you.

So the question is not which framework is better. It is how much of what Django gives you on day one your product actually needs.

Pick FastAPI when the backend's main job is answering clients: a mobile app, a single-page web app, partners, or other services. Typed request and response models mean the API contract lives in the code, and your frontend team can generate a client from the OpenAPI schema instead of reading a wiki.

Pick it when the work is I/O-bound and concurrent: calling a language model and streaming the answer back, holding WebSocket connections open, or fanning out to several third-party APIs per request. Async is the default in FastAPI, not an add-on, so a slow upstream call does not tie up a worker.

And pick it for AI services in particular. The Python AI libraries, model SDKs, and vector database clients sit naturally inside a FastAPI service, and server-sent events for streaming answers take a few lines.

Pick Django when the product is mostly records and the people who manage them: customers, orders, projects, documents, approvals. The ORM and migrations handle a schema with dozens of related tables without ceremony, and the admin gives your team a working back office on the first day.

Pick it when permissions are complicated. Organizations, roles, object-level access, and audit trails are well-trodden ground in Django, and Django REST Framework's permission classes keep those rules in one place rather than scattered through endpoints.

And pick it when the team changing the code in three years may not be the team writing it now. A Django project has a shape any Django developer recognizes. A FastAPI project has whatever shape its first developers gave it.

FastAPI tops most framework benchmarks, and for a hello-world endpoint the gap is real. In a product it rarely decides anything. Requests spend their time in the database, in a third-party API, or in a model call, and a slow query is slow in either framework.

Where FastAPI's async model does matter is concurrency: many open connections that are mostly waiting. Streaming chat, live dashboards, and gateways in front of slow services all fit it. Where Django holds up fine is the typical business app: request in, a few queries, response out. Scale that with more workers, query tuning, and caching, the same way you would scale anything.

If performance is the deciding factor, measure your own workload rather than a benchmark. The options trading platform we built instruments latency across twelve stages for exactly that reason: you find out where the time goes before you change anything.

You do not have to choose once. A common shape is Django for the core records, accounts, and admin, with a FastAPI service beside it for the part that streams, calls models, or holds connections open. The two share a Postgres database or talk over an internal API.

We suggest this most often to teams that already have a Django app and want to add AI. Rewriting a working Django app in FastAPI is almost never worth it. Adding one small service where async genuinely helps usually is.