software
Django vs Flask 2026: Which Python Framework?
Django is a full-featured, batteries-included framework with built-in ORM, admin panel, and authentication, while Flask is a lightweight microframework that requires manual integration of third-party libraries. Django suits large, complex projects; Flask excels for simple applications and APIs.
D
Django
Full-featured Python web framework with batteries included
Full-stack web applications, content management systems, large team projects, applications requiring rapid development with built-in features.
Score71%
VS
F
Flask
Lightweight Python WSGI web framework for building traditional web applications and APIs.
REST APIs, microservices, minimal web applications, developers who prefer flexibility, rapid prototyping, and startups wanting to avoid overhead.
Score71%
Quick Answer
AI SummaryDjango is a full-featured, batteries-included framework with built-in ORM, admin panel, and authentication, while Flask is a lightweight microframework that requires manual integration of third-party libraries. Django suits large, complex projects; Flask excels for simple applications and APIs.
Our Verdict
AI-assistedChoose Django if you're building medium-to-large web applications, need rapid development with built-in features, and prefer convention-over-configuration. Choose Flask if you're creating microservices, simple APIs, lightweight applications, or need maximum flexibility and control over your architecture.
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D
Django
7.7/10
Flask
7.3/10
F
D
Choose Django if
Best pickFull-stack web applications, content management systems, large team projects, applications requiring rapid development with built-in features.
F
Choose Flask if
REST APIs, microservices, minimal web applications, developers who prefer flexibility, rapid prototyping, and startups wanting to avoid overhead.
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Key Differences at a Glance
- Framework Type:Full-featured monolithic framework vs Lightweight microframework
- Built-in Features:✓ Django wins(ORM, admin panel, authentication, migrations, forms, templating vs Core routing and request handling only)
- Learning Curve (hours for beginner):✓ Flask wins(8-15 hours vs 40-60 hours)
Key Facts & Figures
105 numeric metrics compared
| Metric | Django | Flask | Ratio |
|---|---|---|---|
| Average Request Latency(milliseconds) | 200-400ms | — | — |
| Concurrent Connections (single core)(connections) | 100-500 | — | — |
| Time to First Working App(hours) | 1-2 | — | — |
| Package Ecosystem Size(packages) | 500K packages | 300,000+ (PyPI) | |
| Memory Usage (Idle)(MB) | 80-120MB | ~35-45 MB | |
| Average Development Speed (MVP)(weeks) | 3 weeks | — | — |
| Job Openings (Global, 2025)(positions) | 45,000 | — | — |
| Average Page Load Time(seconds) | 145ms | — | — |
| Developer Satisfaction (2025 Survey)(percentage) | 82% | — | — |
| Average Request Response Time(milliseconds) | 65ms | — | — |
| Available Packages/Gems(count) | 500,000+ | 500,000+ | |
| Time to Build Basic MVP(weeks) | 2-3 weeks | — | — |
| Job Market Postings (2025)(estimated count) | 28,000+ | — | — |
| Learning Curve for Beginners(hours to proficiency) | 4-6 months | 20-30 hours | |
| Throughput at Scale (Req/sec)(requests per second) | 2,500 req/sec | — | — |
| GitHub Stars(stars) | 79,400+ stars | ~67,000 stars | |
| Startup Time(seconds) | ~300-500ms | ~150ms | |
| Memory Usage (base)(MB) | ~50MB | — | — |
| Time to First API Endpoint(minutes) | 8-12 hours | 7 minutes | |
| Third-party Packages(packages) | 13,000+ packages | — | — |
| Core Framework Size(KB) | ~2,100 KB | ~60 KB | |
| Request/Response Latency (simple GET)(ms) | 45-65 ms | 25-35 ms | |
| Weekly Downloads (PyPI)(thousands) | 1,200 thousand | 850 thousand | |
| Minimal Project Setup Time(minutes) | 15-20 | 5-10 | |
| Stack Overflow Questions (all-time)(count) | 3,800 thousand | 1,200 thousand | |
| Time to Production (months)(months) | 1.5-2 | — | — |
| Throughput Capacity (requests/sec)(req/sec) | ~5,000 | — | — |
| Lines of Code per Feature(LOC) | 100 | — | — |
| Available Job Openings (US, 2026)(thousands) | ~45K | — | — |
| Memory Usage (baseline app)(MB) | ~150-200 | — | — |
| Learning Curve (hours to 'Hello World')(hours) | 4-6 | — | — |
| Cold Start Time(ms) | 600ms | ~150ms | |
| Base Framework Size(megabytes) | 11 MB | — | — |
| Requests/Second (Throughput)(req/s) | ~1,200 req/s | — | — |
| Learning Time to Proficiency(hours) | 50 hours | — | — |
| Community Size (GitHub Stars)(stars) | 79k stars | — | — |
| Development Speed (Median Project Timeline)(weeks) | 8-12 weeks | — | — |
| Median Response Latency(ms) | 25ms | — | — |
| Requests Per Second (Single Instance)(req/s) | 450 req/s | — | — |
| Time to Production (greenfield project)(days) | 2-3 days | — | — |
| Initial Learning Hours(hours) | 15-25 hours | — | — |
| Memory Usage (hello world app)(MB) | 120MB | — | — |
| Throughput (Requests/Second)(req/sec) | 3,000-5,000 | ~75 (baseline with Gunicorn 4 workers) | |
| Time to First API (minutes)(minutes) | 15-20 | — | — |
| Request Throughput (req/sec, hello-world)(requests/second) | 1,200-1,800 | — | — |
| GitHub Stars (2026)(stars) | 77,000+ | ~67,000 stars | |
| Time to Hello World(minutes) | 8-10 minutes | — | — |
| Available Third-Party Packages(packages) | ~430,000 (PyPI) | — | — |
| Minimum Server RAM Required(MB) | 512 MB | — | — |
| Active Maintainers (2025)(count) | ~2,500 contributors | — | — |
| Request Throughput(requests/second) | 8,000-12,000 req/s | — | — |
| Development Time (basic API)(hours) | 40-60 hours | — | — |
| Ecosystem Size(packages) | 70,000+ packages | — | — |
| Framework Age(years) | 16 years (since 2008) | — | — |
| GitHub Stars (as of 2026)(stars) | 80,000+ stars | 67,300+ stars | |
| Time to First API (Learning Curve)(hours) | 5-10 hours | 5-10 hours | |
| Time Since Initial Release(years) | 18 years (2010) | 18 years (2010) | |
| Related Packages (PyPI)(packages) | ~8,500 | ~8,500 | |
| Cold Start Time (Serverless)(ms) | ~450 ms | ~450 ms | |
| GitHub Stars (Community)(stars) | 68,000+ stars | 68,000+ stars | |
| Available Extensions(count (approx.)) | 2,500+ | 2,500+ | |
| Minimum Project Boilerplate(lines of code) | 5-7 lines | 5-7 lines | |
| Framework Core Size(KB) | ~150 KB | ~150 KB | |
| Average Startup Time(seconds) | ~500 ms | ~500 ms | |
| Market Share Among Web Frameworks(percent) | 70% (Python) | 70% (Python) | |
| Requests Per Second (Concurrent Load)(RPS) | ~2,500 RPS | ~2,500 RPS | |
| Requests Per Second (Benchmark)(req/s) | ~1,200 req/s | ~1,200 req/s | |
| Memory Usage (Single Instance)(MB) | 75 MB | 75 MB | |
| Time to 'Hello World'(minutes) | 3 minutes | 3 minutes | |
| Recommended Learning Duration(weeks) | 2-3 weeks | 2-3 weeks | |
| Job Postings (Global, 2025)(jobs) | 23,500 positions | 23,500 positions | |
| Production Deployments (Est.)(years in market) | 12+ years | 12+ years | |
| Ecosystem Extensions(packages) | 5,000+ | 5,000+ | |
| Time to Build First App(hours) | ~2 hours | ~2 hours | |
| Stack Overflow Questions(questions) | 40,000+ | 40,000+ | |
| Concurrent Connection Limit (Practical)(connections) | 500 optimal | 500 optimal | |
| Production Deployments(organizations) | ~2.5M active | ~2.5M active | |
| Third-Party Extensions Available(plugins) | 10,000+ extensions | 10,000+ extensions | |
| Time to Basic Productivity(hours) | 2-4 hours | 2-4 hours | |
| Active Contributors(developers) | 2,500+ | 2,500+ | |
| Global Job Openings (2024)(positions) | 45,000+ | 45,000+ | |
| Minimum Code Boilerplate (Hello World)(lines) | 12 lines | 12 lines | |
| Setup Time to First Running App(minutes) | 8-12 minutes | 8-12 minutes | |
| Average Community Response Time (GitHub Issues)(hours) | 24-36 hours | 24-36 hours | |
| Throughput (Requests per Second)(req/s) | ~4,000 req/s | ~4,000 req/s | |
| Package Size(MB) | ~2.5 MB | ~2.5 MB | |
| Third-Party Extensions(extensions) | 800+ | 800+ | |
| Production Deployments (Estimated)(count) | 2.5M+ | 2.5M+ | |
| Initial Release Year(year) | 2010 | 2010 | |
| Requests Per Second (Throughput)(req/s) | ~7,500 req/s | ~7,500 req/s | |
| Memory Usage (Baseline)(MB) | ~30MB | ~30MB | |
| Available Packages/Modules(count (millions)) | ~150,000+ PyPI packages | ~150,000+ PyPI packages | |
| GitHub Stars (Popularity Proxy)(stars) | ~67,000 stars | ~67,000 stars | |
| Time to First Hello World(lines of code) | 4 lines | 4 lines | |
| Initial Setup Time(minutes) | 3-5 minutes | 3-5 minutes | |
| Number of Built-in Features(count) | 2 core features | 2 core features | |
| Average Project Setup Lines of Code(lines) | 350 lines (with extras) | 350 lines (with extras) | |
| Third-party Packages Required (typical CRUD)(packages) | 5-8 packages | 5-8 packages | |
| Deployment Complexity Score(1-10 scale) | 6/10 (more decisions) | 6/10 (more decisions) | |
| Performance (Requests/sec, hello world)(req/sec) | 12,500 req/sec | 12,500 req/sec | |
| Job Market Demand (LinkedIn postings 2026)(job postings) | 7,200+ jobs | 7,200+ jobs | |
| Default Dependencies(count) | 1 (werkzeug) | 1 (werkzeug) | |
| Time to 'Hello World' App(lines of code) | 4-5 lines | 4-5 lines | |
| Time to First Production App(days) | 2-3 days | 2-3 days | |
| Available Extensions/Packages(count) | ~90,000 Flask-compatible packages | ~90,000 Flask-compatible packages |
Sourced from publicly available data ·
Key Differences
7 attributes compared head-to-head
D
4DjangoDjango leads2 ties
F
1FlaskDjango
Attribute
Flask
- Full-featured monolithic frameworkFramework TypeLightweight microframework
- ORM, admin panel, authentication, migrations, forms, templating(winner)Built-in FeaturesCore routing and request handling only
- 40-60 hoursLearning Curve (hours for beginner)8-15 hours(winner)
- 150-200 lines(winner)Lines of Code for basic CRUD app300-400 lines
- 382,000+ questions(winner)Community Size (Stack Overflow questions)78,000+ questions
- Django Template Language (DTL)Default Template EngineJinja2
- Medium (guided conventions)(winner)Production deployment complexityHigher (more manual setup required)
- Framework Type
Django
Full-featured monolithic framework
Flask
Lightweight microframework
- Built-in Features
Django
ORM, admin panel, authentication, migrations, forms, templating(winner)
Flask
Core routing and request handling only
- Learning Curve (hours for beginner)
Django
40-60 hours
Flask
8-15 hours(winner)
- Lines of Code for basic CRUD app
Django
150-200 lines(winner)
Flask
300-400 lines
- Community Size (Stack Overflow questions)
Django
382,000+ questions(winner)
Flask
78,000+ questions
- Default Template Engine
Django
Django Template Language (DTL)
Flask
Jinja2
- Production deployment complexity
Django
Medium (guided conventions)(winner)
Flask
Higher (more manual setup required)
Full Comparison
| Attribute | Django | Flask |
|---|---|---|
| Average Request Latency(milliseconds) | 200-400ms | — |
| Average Page Load Time(seconds) | 145ms | — |
| Average Request Response Time(milliseconds) | 65ms | — |
| Throughput at Scale (Req/sec)(requests per second) | 2,500 req/sec | — |
| Startup Time(seconds) | ~300-500ms | ~150ms(winner) |
Show 18 more attributesMemory Usage (base)(MB) ~50MB — Request/Response Latency (simple GET)(ms) 45-65 ms 25-35 ms Throughput Capacity (requests/sec)(req/sec) ~5,000 — Cold Start Time(ms) 600ms ~150ms Requests/Second (Throughput)(req/s) ~1,200 req/s — Median Response Latency(ms) 25ms — Requests Per Second (Single Instance)(req/s) 450 req/s — Throughput (Requests/Second)(req/sec) 3,000-5,000 ~75 (baseline with Gunicorn 4 workers) Request Throughput (req/sec, hello-world)(requests/second) 1,200-1,800 — Request Throughput(requests/second) 8,000-12,000 req/s — Framework Core Size(KB) ~150 KB — Average Startup Time(seconds) ~500 ms — Requests Per Second (Concurrent Load)(RPS) ~2,500 RPS — Requests Per Second (Benchmark)(req/s) ~1,200 req/s — Throughput (Requests per Second)(req/s) ~4,000 req/s — Requests Per Second (Throughput)(req/s) ~7,500 req/s — Memory Usage (Baseline)(MB) ~30MB — Performance (Requests/sec, hello world)(req/sec) 12,500 req/sec — | ||
| Concurrent Connections (single core)(connections) | 100-500 | — |
| Cold Start Time (Serverless)(ms) | ~450 ms | — |
| Concurrent Connection Limit (Practical)(connections) | 500 optimal | — |
| Time to First Working App(hours) | 1-2 | — |
| Time to Build Basic MVP(weeks) | 2-3 weeks | — |
| Minimal Project Setup Time(minutes) | 15-20 | 5-10(winner) |
| Time to Production (months)(months) | 1.5-2 | — |
| Time to Production (greenfield project)(days) | 2-3 days | — |
Show 3 more attributesTime to First API (minutes)(minutes) 15-20 — Minimum Code Boilerplate (Hello World)(lines) 12 lines — Setup Time to First Running App(minutes) 8-12 minutes — | ||
| Package Ecosystem Size(packages) | 500K packages(winner) | 300,000+ (PyPI) |
| ML/AI Library Integration | Excellent (TensorFlow, PyTorch, scikit-learn) | — |
| Available Packages/Gems(count) | 500,000+ | 500,000+ |
| Third-party Packages(packages) | 13,000+ packages | — |
| Available Third-Party Packages(packages) | ~430,000 (PyPI) | — |
Show 8 more attributesEcosystem Size(packages) 70,000+ packages — Related Packages (PyPI)(packages) ~8,500 — Available Extensions(count (approx.)) 2,500+ — Ecosystem Extensions(packages) 5,000+ — Third-Party Extensions(extensions) 800+ — Available Packages/Modules(count (millions)) ~150,000+ PyPI packages — ML/Data Science Library Support(text) Native: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch — Available Extensions/Packages(count) ~90,000 Flask-compatible packages — | ||
| Memory Usage (Idle)(MB) | 80-120MB | ~35-45 MB(winner) |
| Memory Usage (baseline app)(MB) | ~150-200 | — |
| Memory Usage (hello world app)(MB) | 120MB | — |
| Admin Panel Included | Yes (auto-generated) | — |
| Built-in Admin Dashboard | Yes, auto-generated | — |
| Async Request Support | Partial (3.1+) | — |
| Built-in Database ORM(feature) | Django ORM (included) | None (use SQLAlchemy separately) |
| Admin Interface | Auto-generated from models | Requires manual or third-party setup |
Show 8 more attributesBuilt-in ORM Yes (Django ORM with migrations) — Built-in Admin Panel Yes (Django Admin fully featured) — Built-in Authentication Yes, with Django-allauth extension — Built-in Admin Interface Yes, auto-generated — Native Async/Await Support Experimental in Flask 2.0+ — WebSocket Support Extension required (Flask-SocketIO) — Data Science Library Integration Native (NumPy, TensorFlow, Pandas) — Built-in ORM Support Via SQLAlchemy extension — | ||
| Average Development Speed (MVP)(weeks) | 3 weeks | — |
| Job Openings (Global, 2025)(positions) | 45,000 | — |
| Available Job Openings (US, 2026)(thousands) | ~45K | — |
| Async Support Level | Partial (optional, requires setup) | — |
| Native Dependency Injection | No (requires external frameworks) | — |
| Native Async Support | Partial (Django 3.1+) | — |
| Concurrency Model | Synchronous (WSGI) | — |
| Async Support | Requires Flask-APScheduler or manual async setup | — |
Show 1 more attributeAsync/Await Native Support No (WSGI-based) — | ||
| Developer Satisfaction (2025 Survey)(percentage) | 82% | — |
| Job Market Postings (2025)(estimated count) | 28,000+ | — |
| Global Job Openings (2024)(positions) | 45,000+ | — |
| Learning Curve for Beginners(hours to proficiency) | 4-6 months(winner) | 20-30 hours |
| GitHub Stars(stars) | 79,400+ stars(winner) | ~67,000 stars |
| Stack Overflow Questions (all-time)(count) | 3,800 thousand(winner) | 1,200 thousand |
| Community Size (GitHub Stars)(stars) | 79k stars | — |
| GitHub Stars (2026)(stars) | 77,000+(winner) | ~67,000 stars |
| Active Maintainers (2025)(count) | ~2,500 contributors | — |
Show 5 more attributesGitHub Stars (as of 2026)(stars) 80,000+ stars 67,300+ stars GitHub Stars (Community)(stars) 68,000+ stars — Stack Overflow Questions(questions) 40,000+ — Active Contributors(developers) 2,500+ — GitHub Stars (Popularity Proxy)(stars) ~67,000 stars — | ||
| Time to First API Endpoint(minutes) | 8-12 hours | 7 minutes(winner) |
| Core Framework Size(KB) | ~2,100 KB | ~60 KB(winner) |
| Third-party Packages Required (typical CRUD)(packages) | 5-8 packages | — |
| Weekly Downloads (PyPI)(thousands) | 1,200 thousand(winner) | 850 thousand |
| Authentication Built-in | Yes (user model, permissions, groups) | No (use Flask-Login or similar) |
| Lines of Code per Feature(LOC) | 100 | — |
| Learning Curve (hours to 'Hello World')(hours) | 4-6 | — |
| Enterprise Adoption Rate(%) | ~15% | — |
| Base Framework Size(megabytes) | 11 MB | — |
| Admin Panel | Auto-generated included | — |
| Learning Time to Proficiency(hours) | 50 hours | — |
| Time to First API (Learning Curve)(hours) | 5-10 hours | — |
| Learning Curve Difficulty | Easy (1.5/5) | — |
| Development Speed (Median Project Timeline)(weeks) | 8-12 weeks | — |
| Development Time (basic API)(hours) | 40-60 hours | — |
| Automatic API Documentation | Optional (via packages) | No, manual setup required |
| Auto-Documentation Support | Manual integration required | — |
| Built-in Data Validation | No, requires add-ons | — |
Show 6 more attributesTime to 'Hello World'(minutes) 3 minutes — Recommended Learning Duration(weeks) 2-3 weeks — Type Hint Support Optional — Auto Documentation Generation Manual (requires Flask-RESTX, Flasgger) — Time to 'Hello World' App(lines of code) 4-5 lines — Time to First Production App(days) 2-3 days — | ||
| Initial Learning Hours(hours) | 15-25 hours | — |
| Time to Basic Productivity(hours) | 2-4 hours | — |
| NPM Weekly Downloads(downloads) | Not applicable (Python package) | — |
| Market Share Among Web Frameworks(percent) | 70% (Python) | — |
| Production Deployments(organizations) | ~2.5M active | — |
| Production Deployments (Estimated)(count) | 2.5M+ | — |
| Language | Python 3.8+ | — |
| Time to Hello World(minutes) | 8-10 minutes | — |
| Minimum Server RAM Required(MB) | 512 MB | — |
| Framework Age(years) | 16 years (since 2008) | — |
| Time Since Initial Release(years) | 18 years (2010) | — |
| Production Deployments (Est.)(years in market) | 12+ years | — |
| Minimum Python Version(version) | Python 2.7+ (legacy) / 3.4+ | — |
| Minimum Project Boilerplate(lines of code) | 5-7 lines | — |
| Memory Usage (Single Instance)(MB) | 75 MB | — |
| Job Postings (Global, 2025)(jobs) | 23,500 positions | — |
| Time to Build First App(hours) | ~2 hours | — |
| Third-Party Extensions Available(plugins) | 10,000+ extensions | — |
| Built-in Request/Response Handling | Yes (Werkzeug-based) | — |
| Average Community Response Time (GitHub Issues)(hours) | 24-36 hours | — |
| Package Size(MB) | ~2.5 MB | — |
| Default Dependencies(count) | 1 (werkzeug) | — |
| Initial Release Year(year) | 2010 | — |
| Time to First Hello World(lines of code) | 4 lines | — |
| Deployment Without Extra Server(text) | No - requires WSGI server (Gunicorn, uWSGI) | — |
| Deployment Complexity Score(1-10 scale) | 6/10 (more decisions) | — |
| Initial Setup Time(minutes) | 3-5 minutes | — |
| Number of Built-in Features(count) | 2 core features | — |
| Average Project Setup Lines of Code(lines) | 350 lines (with extras) | — |
| Job Market Demand (LinkedIn postings 2026)(job postings) | 7,200+ jobs | — |
| Latest Stable Release(version) | 3.0.0 (Dec 2023) | — |
DDjango
FFlask
Average Request Latency(milliseconds)
200-400ms
—
Average Page Load Time(seconds)
145ms
—
Average Request Response Time(milliseconds)
65ms
—
Throughput at Scale (Req/sec)(requests per second)
2,500 req/sec
—
Startup Time(seconds)
~300-500ms
~150ms
Show 18 more attributes
Memory Usage (base)(MB)
~50MB
—
Request/Response Latency (simple GET)(ms)
45-65 ms
25-35 ms
Throughput Capacity (requests/sec)(req/sec)
~5,000
—
Cold Start Time(ms)
600ms
~150ms
Requests/Second (Throughput)(req/s)
~1,200 req/s
—
Median Response Latency(ms)
25ms
—
Requests Per Second (Single Instance)(req/s)
450 req/s
—
Throughput (Requests/Second)(req/sec)
3,000-5,000
~75 (baseline with Gunicorn 4 workers)
Request Throughput (req/sec, hello-world)(requests/second)
1,200-1,800
—
Request Throughput(requests/second)
8,000-12,000 req/s
—
Framework Core Size(KB)
~150 KB
—
Average Startup Time(seconds)
~500 ms
—
Requests Per Second (Concurrent Load)(RPS)
~2,500 RPS
—
Requests Per Second (Benchmark)(req/s)
~1,200 req/s
—
Throughput (Requests per Second)(req/s)
~4,000 req/s
—
Requests Per Second (Throughput)(req/s)
~7,500 req/s
—
Memory Usage (Baseline)(MB)
~30MB
—
Performance (Requests/sec, hello world)(req/sec)
12,500 req/sec
—
Concurrent Connections (single core)(connections)
100-500
—
Cold Start Time (Serverless)(ms)
~450 ms
—
Concurrent Connection Limit (Practical)(connections)
500 optimal
—
Time to First Working App(hours)
1-2
—
Time to Build Basic MVP(weeks)
2-3 weeks
—
Minimal Project Setup Time(minutes)
15-20
5-10
Time to Production (months)(months)
1.5-2
—
Time to Production (greenfield project)(days)
2-3 days
—
Show 3 more attributes
Time to First API (minutes)(minutes)
15-20
—
Minimum Code Boilerplate (Hello World)(lines)
12 lines
—
Setup Time to First Running App(minutes)
8-12 minutes
—
Package Ecosystem Size(packages)
500K packages
300,000+ (PyPI)
ML/AI Library Integration
Excellent (TensorFlow, PyTorch, scikit-learn)
—
Available Packages/Gems(count)
500,000+
500,000+
Third-party Packages(packages)
13,000+ packages
—
Available Third-Party Packages(packages)
~430,000 (PyPI)
—
Show 8 more attributes
Ecosystem Size(packages)
70,000+ packages
—
Related Packages (PyPI)(packages)
~8,500
—
Available Extensions(count (approx.))
2,500+
—
Ecosystem Extensions(packages)
5,000+
—
Third-Party Extensions(extensions)
800+
—
Available Packages/Modules(count (millions))
~150,000+ PyPI packages
—
ML/Data Science Library Support(text)
Native: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch
—
Available Extensions/Packages(count)
~90,000 Flask-compatible packages
—
Memory Usage (Idle)(MB)
80-120MB
~35-45 MB
Memory Usage (baseline app)(MB)
~150-200
—
Memory Usage (hello world app)(MB)
120MB
—
Admin Panel Included
Yes (auto-generated)
—
Built-in Admin Dashboard
Yes, auto-generated
—
Async Request Support
Partial (3.1+)
—
Built-in Database ORM(feature)
Django ORM (included)
None (use SQLAlchemy separately)
Admin Interface
Auto-generated from models
Requires manual or third-party setup
Show 8 more attributes
Built-in ORM
Yes (Django ORM with migrations)
—
Built-in Admin Panel
Yes (Django Admin fully featured)
—
Built-in Authentication
Yes, with Django-allauth extension
—
Built-in Admin Interface
Yes, auto-generated
—
Native Async/Await Support
Experimental in Flask 2.0+
—
WebSocket Support
Extension required (Flask-SocketIO)
—
Data Science Library Integration
Native (NumPy, TensorFlow, Pandas)
—
Built-in ORM Support
Via SQLAlchemy extension
—
Average Development Speed (MVP)(weeks)
3 weeks
—
Job Openings (Global, 2025)(positions)
45,000
—
Available Job Openings (US, 2026)(thousands)
~45K
—
Async Support Level
Partial (optional, requires setup)
—
Native Dependency Injection
No (requires external frameworks)
—
Native Async Support
Partial (Django 3.1+)
—
Concurrency Model
Synchronous (WSGI)
—
Async Support
Requires Flask-APScheduler or manual async setup
—
Show 1 more attribute
Async/Await Native Support
No (WSGI-based)
—
Developer Satisfaction (2025 Survey)(percentage)
82%
—
Job Market Postings (2025)(estimated count)
28,000+
—
Global Job Openings (2024)(positions)
45,000+
—
Learning Curve for Beginners(hours to proficiency)
4-6 months
20-30 hours
GitHub Stars(stars)
79,400+ stars
~67,000 stars
Stack Overflow Questions (all-time)(count)
3,800 thousand
1,200 thousand
Community Size (GitHub Stars)(stars)
79k stars
—
GitHub Stars (2026)(stars)
77,000+
~67,000 stars
Active Maintainers (2025)(count)
~2,500 contributors
—
Show 5 more attributes
GitHub Stars (as of 2026)(stars)
80,000+ stars
67,300+ stars
GitHub Stars (Community)(stars)
68,000+ stars
—
Stack Overflow Questions(questions)
40,000+
—
Active Contributors(developers)
2,500+
—
GitHub Stars (Popularity Proxy)(stars)
~67,000 stars
—
Time to First API Endpoint(minutes)
8-12 hours
7 minutes
Core Framework Size(KB)
~2,100 KB
~60 KB
Third-party Packages Required (typical CRUD)(packages)
5-8 packages
—
Weekly Downloads (PyPI)(thousands)
1,200 thousand
850 thousand
Authentication Built-in
Yes (user model, permissions, groups)
No (use Flask-Login or similar)
Lines of Code per Feature(LOC)
100
—
Learning Curve (hours to 'Hello World')(hours)
4-6
—
Enterprise Adoption Rate(%)
~15%
—
Base Framework Size(megabytes)
11 MB
—
Admin Panel
Auto-generated included
—
Learning Time to Proficiency(hours)
50 hours
—
Time to First API (Learning Curve)(hours)
5-10 hours
—
Learning Curve Difficulty
Easy (1.5/5)
—
Development Speed (Median Project Timeline)(weeks)
8-12 weeks
—
Development Time (basic API)(hours)
40-60 hours
—
Automatic API Documentation
Optional (via packages)
No, manual setup required
Auto-Documentation Support
Manual integration required
—
Built-in Data Validation
No, requires add-ons
—
Show 6 more attributes
Time to 'Hello World'(minutes)
3 minutes
—
Recommended Learning Duration(weeks)
2-3 weeks
—
Type Hint Support
Optional
—
Auto Documentation Generation
Manual (requires Flask-RESTX, Flasgger)
—
Time to 'Hello World' App(lines of code)
4-5 lines
—
Time to First Production App(days)
2-3 days
—
Initial Learning Hours(hours)
15-25 hours
—
Time to Basic Productivity(hours)
2-4 hours
—
NPM Weekly Downloads(downloads)
Not applicable (Python package)
—
Market Share Among Web Frameworks(percent)
70% (Python)
—
Production Deployments(organizations)
~2.5M active
—
Production Deployments (Estimated)(count)
2.5M+
—
Language
Python 3.8+
—
Time to Hello World(minutes)
8-10 minutes
—
Minimum Server RAM Required(MB)
512 MB
—
Framework Age(years)
16 years (since 2008)
—
Time Since Initial Release(years)
18 years (2010)
—
Production Deployments (Est.)(years in market)
12+ years
—
Minimum Python Version(version)
Python 2.7+ (legacy) / 3.4+
—
Minimum Project Boilerplate(lines of code)
5-7 lines
—
Memory Usage (Single Instance)(MB)
75 MB
—
Job Postings (Global, 2025)(jobs)
23,500 positions
—
Time to Build First App(hours)
~2 hours
—
Third-Party Extensions Available(plugins)
10,000+ extensions
—
Built-in Request/Response Handling
Yes (Werkzeug-based)
—
Average Community Response Time (GitHub Issues)(hours)
24-36 hours
—
Package Size(MB)
~2.5 MB
—
Default Dependencies(count)
1 (werkzeug)
—
Initial Release Year(year)
2010
—
Time to First Hello World(lines of code)
4 lines
—
Deployment Without Extra Server(text)
No - requires WSGI server (Gunicorn, uWSGI)
—
Deployment Complexity Score(1-10 scale)
6/10 (more decisions)
—
Initial Setup Time(minutes)
3-5 minutes
—
Number of Built-in Features(count)
2 core features
—
Average Project Setup Lines of Code(lines)
350 lines (with extras)
—
Job Market Demand (LinkedIn postings 2026)(job postings)
7,200+ jobs
—
Latest Stable Release(version)
3.0.0 (Dec 2023)
—
Pros & Cons
10 pros·4 cons across both
D
F
D
Django
+5-2
Pros
- Complete admin interface generated automatically from models
- Powerful built-in ORM with migrations system for database management
- Integrated user authentication and permission system
- Comprehensive documentation and 20+ years of ecosystem maturity
- DRY (Don't Repeat Yourself) architecture reduces boilerplate code
Cons
- Steeper learning curve for beginners (40-60 hours)
- Opinionated structure may feel restrictive for simple projects
F
Flask
+5-2
Pros
- Minimal learning curve (8-15 hours for beginners)
- Highly flexible - choose your own libraries and architecture
- Excellent for building REST APIs and microservices
- Lightweight codebase allows deep customization
- Perfect for prototyping and small-to-medium projects
Cons
- Requires manual integration of ORM, authentication, and admin tools
- Larger ecosystem means more decision-making overhead
Frequently Asked Questions
5 questions
Flask is better for absolute beginners due to its smaller scope and simpler learning curve (8-15 hours vs 40-60 hours). However, if you're willing to invest time upfront, Django's guided structure actually accelerates learning for building complete applications.
Resources & Learn More
Curated sources to dive deeper
Where to Buy
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Wikipedia
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