Android SDK vs Django vs Node.js

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Android SDK
Android SDK

7.8K
5.7K
+ 1
774
Django
Django

8.7K
6.5K
+ 1
2.9K
Node.js
Node.js

33.7K
27.7K
+ 1
7.9K
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What is Android SDK?

Android provides a rich application framework that allows you to build innovative apps and games for mobile devices in a Java language environment.

What is Django?

Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design.

What is Node.js?

Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices.
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    What are some alternatives to Android SDK, Django, and Node.js?
    Android Studio
    Android Studio is a new Android development environment based on IntelliJ IDEA. It provides new features and improvements over Eclipse ADT and will be the official Android IDE once it's ready.
    Ionic
    Free and open source, Ionic offers a library of mobile and desktop-optimized HTML, CSS and JS components for building highly interactive apps. Use with Angular, React, Vue, or plain JavaScript.
    React Native
    React Native enables you to build world-class application experiences on native platforms using a consistent developer experience based on JavaScript and React. The focus of React Native is on developer efficiency across all the platforms you care about - learn once, write anywhere. Facebook uses React Native in multiple production apps and will continue investing in React Native.
    Flutter
    Flutter is a mobile app SDK to help developers and designers build modern mobile apps for iOS and Android.
    Xamarin
    Xamarin’s Mono-based products enable .NET developers to use their existing code, libraries and tools (including Visual Studio*), as well as skills in .NET and the C# programming language, to create mobile applications for the industry’s most widely-used mobile devices, including Android-based smartphones and tablets, iPhone, iPad and iPod Touch.
    See all alternatives
    Decisions about Android SDK, Django, and Node.js
    Node.js
    Node.js
    Python
    Python
    MySQL
    MySQL
    Memcached
    Memcached
    nginx
    nginx
    RabbitMQ
    RabbitMQ
    Redis
    Redis
    Django
    Django
    Tornado
    Tornado
    Varnish
    Varnish
    HAProxy
    HAProxy

    Around the time of their Series A, Pinterest’s stack included Python and Django, with Tornado and Node.js as web servers. Memcached / Membase and Redis handled caching, with RabbitMQ handling queueing. Nginx, HAproxy and Varnish managed static-delivery and load-balancing, with persistent data storage handled by MySQL.

    See more
    Node.js
    Node.js
    Python
    Python
    React
    React
    Django
    Django

    In late 2015, following the Series G, Pinterest began migrating their web experience to React, primarily because they “found React rendered faster than our previous template engine, had fewer obstacles to iterating on features and had a large developer community.”

    The legacy setup consistent of Django, Python and Jinja on the backend, with Nunjucks handling template rendering on the client side. They wanted to move to React for handling template rendering across the board, but if they “switched the client-side rendering engine from Nunjucks to React, [they’d] also have to switch [their] server-side rendering, so they could share the same template syntax.”

    They decided on an iterative approach that consolidated a single template rendering engine between client and server, since “If the server could interpret JavaScript, and use Nunjucks to render templates and share our client-side code, we could then move forward with an iterative migration to React.” The team decided to stand up a Node process, behind Nginx, and interpret JavaScript server-side.

    Now, when a user agent makes a request, a latent module render requests that it needs data via an API call. Concurrently, a separate network call is made “to a co-located Node process to render the template as far as it can go with the data that it has.”

    Node then responds with rendered templates, and along with a “holes” array to indicate what data was still needed to complete the render. Finally, the Python webapp makes an API call to fetch the remaining data, and each module is sent back to Node as completely independent module requests/in parallel/.

    With this framework in place, Pinterest developers are in the process of replacing Nunjucks code with React components throughout the codebase.

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    Zarema Khalilova
    Zarema Khalilova
    Frontend Team Lead at Uploadcare · | 8 upvotes · 57K views
    atUploadcareUploadcare
    Django
    Django
    Node.js
    Node.js
    React
    React
    Gatsby
    Gatsby
    Netlify
    Netlify
    #Frontend
    #StaticSiteGenerators
    #StaticWebHosting

    Since 2011 our frontend was in Django monolith. However, in 2016 we decide to separate #Frontend from Django for independent development and created the custom isomorphic app based on Node.js and React. Now we realized that not need all abilities of the server, and it is sufficient to generate a static site. Gatsby is suitable for our purposes. We can generate HTML from markdown and React views very simply. So, we are updating our frontend to Gatsby now, and maybe we will use Netlify for deployment soon. This will speed up the delivery of new features to production.

    #StaticSiteGenerators #StaticWebHosting

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    Julien DeFrance
    Julien DeFrance
    Principal Software Engineer at Tophatter · | 16 upvotes · 837.5K views
    atSmartZipSmartZip
    Rails
    Rails
    Rails API
    Rails API
    AWS Elastic Beanstalk
    AWS Elastic Beanstalk
    Capistrano
    Capistrano
    Docker
    Docker
    Amazon S3
    Amazon S3
    Amazon RDS
    Amazon RDS
    MySQL
    MySQL
    Amazon RDS for Aurora
    Amazon RDS for Aurora
    Amazon ElastiCache
    Amazon ElastiCache
    Memcached
    Memcached
    Amazon CloudFront
    Amazon CloudFront
    Segment
    Segment
    Zapier
    Zapier
    Amazon Redshift
    Amazon Redshift
    Amazon Quicksight
    Amazon Quicksight
    Superset
    Superset
    Elasticsearch
    Elasticsearch
    Amazon Elasticsearch Service
    Amazon Elasticsearch Service
    New Relic
    New Relic
    AWS Lambda
    AWS Lambda
    Node.js
    Node.js
    Ruby
    Ruby
    Amazon DynamoDB
    Amazon DynamoDB
    Algolia
    Algolia

    Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

    I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

    For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

    Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

    Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

    Future improvements / technology decisions included:

    Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

    As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

    One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

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    Divine Bawa
    Divine Bawa
    at PayHub Ghana Limited · | 13 upvotes · 155.5K views
    Node.js
    Node.js
    GraphQL
    GraphQL
    MySQL
    MySQL
    Prisma
    Prisma
    graphql-yoga
    graphql-yoga
    React
    React
    styled-components
    styled-components
    Next.js
    Next.js
    Apollo
    Apollo

    I just finished a web app meant for a business that offers training programs for certain professional courses. I chose this stack to test out my skills in graphql and react. I used Node.js , GraphQL , MySQL for the #Backend utilizing Prisma as a database interface for MySQL to provide CRUD APIs and graphql-yoga as a server. For the #frontend I chose React, styled-components for styling, Next.js for routing and SSR and Apollo for data management. I really liked the outcome and I will definitely use this stack in future projects.

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    Francisco Quintero
    Francisco Quintero
    Tech Lead at Dev As Pros · | 7 upvotes · 132.9K views
    atDev As ProsDev As Pros
    Node.js
    Node.js
    Rails
    Rails
    Amazon EC2
    Amazon EC2
    Heroku
    Heroku
    RuboCop
    RuboCop
    JavaScript
    JavaScript
    ESLint
    ESLint
    Slack
    Slack
    Twist
    Twist

    For many(if not all) small and medium size business time and cost matter a lot.

    That's why languages, frameworks, tools, and services that are easy to use and provide 0 to productive in less time, it's bes