Django and FastAPI are both common choices when a Python team starts a new backend. Django is the full-stack option, shipping an object-relational mapper (ORM), migrations, authentication, and an admin interface as one integrated stack.
FastAPI is the API-first option, turning Python type hints into request validation and documentation and leaving the data layer to the team that builds on it.
Both support async workloads. Choose based on the components you want integrated and those your team will select and maintain.
Key takeaways:
Django integrates an ORM, migrations, authentication, and a model-based admin. FastAPI leaves those choices to your team.
Both support async requests. The server, middleware, and libraries determine how much concurrency an application gains.
Django's admin is useful for staff editing records. FastAPI can also own its database and use third-party admin tools.
Compare representative requests with equivalent validation and database work before making performance a deciding factor.
Copy link to headingWhat are the differences between Django and FastAPI?
The main difference between Django and FastAPI is how much each framework includes. Django bundles a database layer, migrations, authentication, an admin interface, and forms, all designed to work together.
FastAPI handles routing and request validation on top of Starlette and Pydantic, and leaves the database, auth, and admin to libraries the team chooses.
Both frameworks support the Asynchronous Server Gateway Interface (ASGI). Django also supports the Web Server Gateway Interface (WSGI), but its full async request stack requires ASGI and async-compatible middleware. Synchronous components can still require adapters and worker threads.
Copy link to headingCompare the components each framework provides
Database integration, staff tooling, and request handling affect both the initial build and ongoing maintenance.
Django REST Framework and Django Ninja add dedicated API layers to Django, with Ninja providing type-hint validation. FastAPI can use SQLAlchemy and Alembic for database access and migrations.
Django's bundled components follow shared conventions. Teams using either framework still need to test the third-party integrations they select.
Copy link to headingRequest model and concurrency
Both frameworks accept def and async def handlers. FastAPI sends a plain def handler to a threadpool and runs an async def handler on the event loop.
Django can run an async view under WSGI using a one-off event loop. That view can await concurrent calls, but it still occupies its WSGI worker for the request. Use ASGI and compatible middleware to gain concurrency across waiting requests.
Copy link to headingDatabase layer and migrations
Django integrates its ORM with migrations and the admin. Model changes feed makemigrations, and registered models supply the admin's form fields. With FastAPI, you choose the database library and configure schema migrations, connection pooling, and session cleanup.
That flexibility lets each service pick its own tools, and it also means two FastAPI codebases in the same company can end up with different data layers.
Copy link to headingAdmin interface and internal tooling
Registering a Django model enables a create, read, update, and delete (CRUD) interface for authorized staff. The admin works well for editing records; approval flows or interfaces organized around a business process may need custom views.
FastAPI has no equivalent in core. An internal data interface becomes something the team builds, buys, or goes without.
Copy link to headingValidation and API schema
Django includes forms and ModelForms for validation. API libraries such as Django REST Framework add serializers, including ModelSerializer for deriving fields from a Django model. FastAPI uses Pydantic models to describe and validate API data.
Sharing model definitions with generated OpenAPI schemas reduces duplicated declarations. In FastAPI, declare a response model or return type to validate and document output; returning a Response directly bypasses that processing. In either framework, review which database fields the API exposes.
Copy link to headingBackground work and task execution
Django's Tasks framework defines and enqueues work through a configured backend. Production needs a backend that supplies durable storage and execution; the bundled backends are intended for development and testing.
FastAPI's BackgroundTasks runs work in the same process after sending the response. It has no durable queue to recover unfinished work after a process failure, so jobs that must survive restarts need separate infrastructure.
Copy link to headingHow Django works for teams shipping data-backed products
Django's integrated components help when the same application needs persistent data, account management, server-rendered pages, and staff tools. You can also use Django for an API-only service and select the components it needs.
Django 6.1 shipped in August 2026, while 5.2 remains the current long-term support release. The project moves to an annual release cycle in January 2028 with three years of support per release.
Copy link to headingThe conventions Django is built on
Django makes the same structural decisions for every project, so a team doesn't have to. These conventions shape how a Django codebase is organized:
Models and migrations: Model classes describe data and relationships.
makemigrationscreates change files, andmigrateapplies them to the database.Feature apps: Projects can organize areas such as billing or accounts into apps containing related models, views, and migrations.
Settings: The settings module configures databases, installed apps, middleware, and security. It can import shared or environment-specific settings.
URL routing: URLconfs map patterns to views and can include other URLconfs as the application grows.
Mixed request styles: Sync and async views can coexist. Django adapts calls where necessary, with the concurrency constraints described above.
Copy link to headingWhere Django is strong and where it falls short
Django's strengths show most in applications where staff, not only code, create and edit data. It skips the setup work of choosing and wiring an ORM, auth, and admin.
The advantages worth relying on:
Generated admin forms: Django derives the default form from a registered model's editable fields. Explicit field lists and custom forms give you control over what staff can change.
Integrated auth and permissions: Django includes users, groups, sessions, and model-level permissions. Your application still needs to enforce those permissions and implement any object-level access rules.
Versioned migration history: Every schema change is a file in the repository, so anyone can see how the database reached its current shape.
Built-in security protections: Django supplies CSRF and clickjacking middleware plus password hashing. Before deployment, review the production checklist, including
DEBUG, allowed hosts, secret keys, and HTTPS settings.
Django's limitations come from two places. Some parts of its async support are still incomplete, and the default project includes features an API-only service won't use:
Transactions are still synchronous: Transactional code runs as a synchronous function called through
sync_to_async().Connections in async mode: Disable
CONN_MAX_AGEand use pooling from the database backend or a third-party pooler.Sync middleware can limit concurrency: Synchronous middleware in an ASGI request path requires Django to keep a thread available for that request. Check third-party middleware before relying on an async request stack.
The starter includes optional components:
startprojectenables admin, sessions, messages, and static files. Keep the components your API uses and remove others when that reduces maintenance.
Load-test the full request path with representative database calls and middleware to expose concurrency limits from adapters, threads, or other dependencies.
Copy link to headingWorkloads that suit Django
Three kinds of application play to Django's strengths:
Applications operated by staff: Support agents correcting orders or editors managing records can use Django's model-based admin. Workflows with approvals or specialized screens may need custom views.
Products with a relational domain model: Related tables, constraints, migrations, and admin forms share Django model definitions. This reduces the number of separate conventions the team has to coordinate.
Server-rendered applications with accounts: Templates, forms, sessions, and authentication views support login and password-reset flows. The team supplies page templates and application-specific access rules.
Django also runs API-only services well, though fewer of its bundled pieces earn their place there.
Copy link to headingHow FastAPI works for teams building API-first services
FastAPI is an ASGI web framework that derives request validation, response serialization, and an OpenAPI schema from Python type annotations. It is built on Starlette for routing and Pydantic for data handling.
FastAPI's scope is the API itself, meaning what a service accepts and what it returns. There is no ORM to adopt and no admin to configure, and templating is an optional Jinja2 integration rather than a core layer.
FastAPI also includes Server-Sent Events and native OpenTelemetry integration. Telemetry sender packages come with fastapi[standard]; configure a monitoring destination to receive the traces, metrics, and logs.
Copy link to headingWhat happens when a request reaches FastAPI
FastAPI reads an endpoint's parameter declarations and type hints to determine its inputs. Path and query parameters, headers, and request bodies can be declared and validated before the handler runs.
Invalid data or a missing required field produces a structured HTTP 422 response by default. Accepted values may be converted to the declared types, and the same declarations feed the OpenAPI schema shown at /docs.
FastAPI moves a plain def handler to a threadpool so the event loop remains available during a blocking database call. Directly calling a synchronous helper inside an async def handler keeps that work on the event loop. Use async clients or explicitly offload blocking work to prevent it from stalling other requests.
Copy link to headingWhere FastAPI is strong and where it falls short
FastAPI fits APIs with explicit input and output contracts. Its async handlers can serve network-heavy requests concurrently when they use nonblocking libraries, and its type annotations connect validation with generated documentation.
The strengths that justify assembling the rest:
Dependency injection in the signature: Database sessions, auth checks, and shared clients are declared with
Depends()and resolved per request, so shared logic like auth can be swapped out in tests.Concurrent network work: Async handlers can await several upstream calls or stream responses while the event loop serves other requests, provided the libraries they call do not block it.
Editor-level type safety: The annotations that validate requests also feed autocompletion and static checking across the codebase.
Replaceable components: Choose the data layer, authentication system, and background execution tools to suit the service.
Your team supplies the components FastAPI does not bundle:
Admin tooling: Add a third-party admin package or build the screens staff need.
Account management: FastAPI provides security helpers, but the team must supply user storage, permission rules, and any login or recovery flows.
Migrations are a separate tool: Schema history depends on Alembic or an equivalent, chosen and configured separately from the ORM.
Version upgrades: FastAPI's 0.x minor releases can include breaking changes. Pin the version and run application tests when upgrading.
Budget maintenance for the selected database, authentication, and admin integrations alongside framework upgrades.
Copy link to headingWorkloads that suit FastAPI
Three kinds of service play to FastAPI's strengths:
Model APIs and streaming: Async clients can await remote model services and stream their output through Server-Sent Events. Local inference needs capacity planning because computation can block a request worker.
Internal APIs between services: For a service whose only consumers are other services, the generated OpenAPI schema replaces a hand-written API spec. Consuming teams generate typed clients from it instead of reading code.
Endpoints that combine several upstream calls: An endpoint that calls four upstream systems and composes the results benefits from concurrent awaits in a single process. The framework's overhead is small next to the time spent waiting on those calls.
FastAPI also handles general CRUD APIs well, with the database layer and migrations chosen by the team.
Copy link to headingDjango or FastAPI? How to choose for your next service
Start with required components and your team's existing integrations:
Choose Django when its ORM, account system, and admin solve a substantial part of the application.
Choose FastAPI when typed API contracts and the freedom to select supporting libraries match the service's requirements.
Either framework can own application data. Staff workflows, existing code, and maintenance capacity help decide which combination fits.
Copy link to headingCompare the data tools you need
Django connects queries, migrations, and the admin through one model definition. FastAPI lets you choose a database library and migration tool that fit an existing schema or team standard.
Copy link to headingCount the cost of building your own admin
Include staff tools in the initial scope. Determine whether users need to edit individual records, approve changes, or follow a multi-step process.
Django's admin can cover record-oriented work. More specialized workflows may require custom screens with either framework, so estimate that work before treating the bundled admin as the deciding advantage.
Copy link to headingCompare where each learning curve gets steep
Django introduces a shared set of concepts: apps, models, migrations, settings, and the request cycle. Familiarity with those conventions can carry across projects, though each application adds its own design choices.
FastAPI starts with route functions and type annotations. Production work also requires understanding async behavior and the chosen database, migration, and authentication tools. Existing team experience can change which framework takes less effort to adopt.
Copy link to headingPlan for running both as the system grows
Django and FastAPI can serve different parts of the same system. For example, Django can provide the main application and admin while a FastAPI service handles a separate streaming API.
If both access the same tables, designate one migration history and coordinate schema changes with both services. makemigrations generates files; migrate applies them. Agree which service may write each set of records so direct database access does not bypass application rules.
Copy link to headingHow Vercel runs Django and FastAPI for Python teams
Both frameworks run on Vercel Functions using the Python runtime. Vercel detects Django through manage.py and its configured WSGI or ASGI application. FastAPI detection looks for an app instance at a supported entrypoint, with custom locations configurable in pyproject.toml.
Copy link to headingI/O wait isn't billed as active CPU on Fluid compute
Async handlers can let other requests progress while waiting for a database or upstream API. Their effect on cost depends on the billing model and how much work each instance can serve.
With Fluid compute, Python requests can share an instance. Active CPU billing excludes time waiting on external I/O. Provisioned Memory remains billed until the last in-flight request completes, so overlapping requests can share that allocation.
Copy link to headingBackground jobs get a durable queue inside the project
Django's Tasks API requires a production execution backend. Vercel Queues, currently in beta, provides durable topics and a Python SDK for applications that send and consume messages directly.
For Celery applications, Vercel's Celery integration builds configured subscribers as queue-triggered Functions. It uses Vercel Queues as the broker, and each task remains subject to Function duration and bundle limits. Django Tasks needs its own compatible backend integration.
Copy link to headingPrecompiled bytecode shortens Python cold starts
Importing Python source can add cold-start work when cached bytecode is unavailable. Precompilation removes that source-compilation step, while module execution and other initialization still contribute to startup time.
Vercel precompiles Python bytecode during the build. In Vercel's benchmark, cold starts for a median-sized function fell from 2.8s to 1.3s. Gains may be smaller near the bundle size limit because only the bytecode that fits is included.
Copy link to headingThe front end and the Python API ship from one project
Frontend and backend changes sometimes depend on each other, such as an API response change paired with a new page. Deploying them together gives you a preview in which to test that combination.
Vercel Services, currently in beta, lets a Next.js frontend and Python backend share one project and deployment. Define each service and its routing, then test the frontend's API calls in the preview before promoting the deployment.
Copy link to headingDeploy your chosen framework
Follow the Django deployment guide or FastAPI deployment guide to configure the entrypoint, dependencies, and environment. Confirm database access and any migrations or static-file setup before sending production traffic.
Start a project from your repository or browse Python templates.
Copy link to headingFrequently asked questions about Django vs FastAPI
Copy link to headingIs Django's async support production-ready?
Yes. Django supports production async views and database APIs, but the full async request stack requires ASGI and compatible middleware. Transaction blocks still need synchronous code, and blocking dependencies must be handled appropriately. Test the complete request path under the concurrency your application expects.
Copy link to headingCan you use FastAPI with the Django ORM?
Yes, but FastAPI does not initialize Django or manage its ORM connection lifecycle for you. Configure Django, initialize its app registry, and handle connections and synchronous operations appropriately.
Django Ninja is another option when you want Pydantic validation and OpenAPI documentation within an existing Django application.
Copy link to headingIs FastAPI faster than Django?
Benchmark results depend on the work each implementation does. Compare equivalent database queries, validation, middleware, and worker settings, then measure latency and throughput at representative concurrency. Framework-only results do not predict your application's response time.
Copy link to headingShould an existing Django application migrate to FastAPI?
Consider migration when a measured requirement justifies replacing the existing application. Account for the ORM, migrations, admin, permissions, and integrations that Django currently provides.
Extracting a bounded API can preserve those investments. If authentication moves, support stored password hashes or retain the existing identity system.