Django
Python's batteries-included web framework. ORM, authentication, admin interface, migrations, and security middleware ship out of the box.
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Batteries included, production proven
Django assembles what every data-backed product needs: an ORM with a first-class migration system, authentication and permissions, security middleware with sound defaults, and an admin interface generated directly from the models. These parts ship and evolve together, reviewed against each other in every release.
Django REST Framework extends the same conventions to APIs, and Celery carries the background work beside them. Because Django is Python, the product shares a language with the data ecosystem around it, so pipelines, analysis and the application can live in one codebase with one set of engineers.
Django is the right choice when a product has accounts, permissions, relational data and an operations surface to run. It is the wrong choice for a single-purpose API service with none of those, where its batteries travel as dead weight; FastAPI is the lighter Python answer there, and the choice between the two is set out on our Python page.
In the 2025 Stack Overflow Developer Survey, 12.6% of respondents reported working with Django in the past year.
Django designates a long-term support release every two years, and each LTS receives security updates for three years.
- Data Platforms
- Internal Tools
- REST APIs
- Admin Dashboards
Our Django capabilities
Django REST Framework APIs
Django REST Framework builds APIs from serialisers, viewsets and JWT authentication, with pagination and filtering configured rather than written by hand. The OpenAPI schema is generated from the code itself, keeping the documentation aligned with the endpoints it describes.
- DRF
- OpenAPI
- JWT
ORM & data modelling
Models declare the schema once; migrations version every change and apply in order across environments. The same declarations drive complex queries, the admin interface, and multi-database routing where reads belong on a replica.
- Django ORM
- Migrations
- Admin
Async views & task processing
Async views serve I/O-bound endpoints that spend their time waiting on other systems. Anything slower than a request moves to Celery on Redis: reports, email, long imports, with retry policies and monitoring so a failed task is seen and re-run instead of lost.
- Celery
- Redis
- async/await
Why Adaca for Django?
Enterprise data platforms
Internal data management tools and regulatory reporting for financial services clients.
DRF API architecture
Versioning, throttling, custom permissions, and OpenAPI documentation for multi-client APIs.
Django security hardening
CSP headers, HSTS, rate limiting, and automated dependency scanning via pip-audit.
Database performance tuning
Query profiling with django-debug-toolbar, identifying N+1 queries and slow aggregations.
Celery & async workflows
Retry policies, dead letter queues, and Flower monitoring for reliable background jobs.
Django-to-FastAPI migration
Incremental migration to FastAPI for performance-critical endpoints while keeping Django for admin and auth.
How We Staff It
The common Django profile is a back-end engineer with Django REST Framework depth who also reads the data layer well, because Django work is usually data-heavy: APIs over a relational schema, reporting, an admin surface for operations. Where a product pairs Django with a React front end, the disciplines are staffed as two people.
Common Questions
We run a Django monolith, should we move hot endpoints to FastAPI?
Only after profiling shows the framework is the constraint, which is uncommon. Most slow Django endpoints spend their time in queries: N+1 access patterns, missing indexes, aggregations that belong in the database. Fixing those costs a fraction of a migration.
Where profiling does point at the framework, model serving or heavy fan-out under concurrency, we carve that endpoint out to FastAPI and leave Django owning authentication, the ORM and the admin. The seam stays narrow and the monolith keeps its job.
Is Django a sound base for a system we will run for ten years?
Few frameworks are built more deliberately for long ownership. APIs deprecate slowly with warnings across releases, upgrades are documented and incremental, and the ORM, authentication and admin that products lean on have been stable for years.
The upgrades that hurt are the ones deferred for years. Tracking LTS releases as routine maintenance keeps each step small; skipping them converts a set of small steps into one large project.
Does Django suit AI-accelerated development?
Yes, through two mechanisms at once. Python has the densest public corpus of any language, and Django adds a layer of convention on top: models, views, serialisers and migrations take the same shape across thousands of public projects, so little of a Django application is code the tooling has never seen the like of.
The characteristic failure is the ORM's implicit behaviour: reverse relations, signals and middleware effects invisible at the call site. Type hints through django-stubs and tests over the model layer give an agent the signal to catch those before they ship.
Can one engagement cover both Django and the data work around it?
Often, yes. The bench behind our Django work spans Django REST Framework and data engineering, so one engineer can frequently own the API together with the Celery pipelines and reporting behind it. Where the brief needs deeper specialisation, streaming infrastructure for instance, dedicated recruitment covers it, and engagements begin at a single engineer either way.