Android vs. iOS: ON WHICH PLATFORM YOU SHOULD BUILD MOBILE APP FIRST

In this era of mobility and changing time, development is taking place faster than anytime. We have a lot to dig in. 

Mobile application is ruling the era and this era is being ruled by Android and iOS. In the fourth quarter of 2020, around 2.9 million apps were available in the Apple App Store. It would be astonishing for you to know that till February 2021, Android has 71.9% Market share Worldwide. 

Now you can imagine how much good you will make when you choose to build an application of your own. 

If you’re creating an application, developing for iOS or Android is one of the first decisions you need to make.

Why can’t you develop mobile application on both platforms? 

Well you can, but it’s too risky if you are just starting with your business. 

We know that your ultimate goal is to launch an application on both platforms, before you decide anything, you need to think about the risk factors you’ll face if you select both platforms. 

Creating an app in both iOS and Android can cost you way too much. Here, you’ll be putting a high amount of money at stake. 

Instead of that, you can launch your app on any one platform, once it is successful; you can launch the app on another platform. 

So, how will you decide between Android and iOS to launch your app?

There are pros and cons of both platforms, but your choice depends on 7 factors:

  1. Hardware Requirement
  2. Target Audience
  3. License Issue 
  4. Features
  5. Integrated Development Environment
  6. Monetization 

Without wasting any time, let’s start with how these factors will affect your application. 

Let’s start!

#1 Hardware Requirements

Depending on the country in which you are, the hardware requirements are obvious to have or not so obvious to have.

In countries like India Windows is the dominant operating system, rather than US and Uk, where Mac Operating systems are mostly preferred. For the people in the USA and UK, it is pretty much common to develop iOS App rather than Android App. 

In India, Android Mobile Application development is much more preferred because the hardware you need is easily accessible and cheaper than iOS hardwares. 

The hurdle you’ll face is, for the MAC or iOS Mobile Application Development, you’ll need to have an iMac, Mac Mini or Macbook Pro. 

Where Android hardware is easier to get or upgrade. 

Thus, it is your choice to choose the hardware requirement according to your need. 

Important Features for perfect hardware for developing Mobile Application:

  • Top processor (Core i9/ Ryzen 9 Processor is new in market). Choose i3 Processor / ryzen 3 Minimum. 
  • Minimum 8GB RAM is preferred, if you purchase 16 GB RAM, it will be a good decision. 
  • Minimum 256GB SSD Hard Disk is required.

 

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LogicRays Recommendation:

Whatever you choose, choose wisely because your Hardware requirement will be the base of your Application and both Android and iOS have their pros and cons. 

If you got big bucks to spend for your application, go for iOS App Development

And, if you want to make your Application under the budget with good features, Android App Development is what you should prefer. 

#2 Target Audience 

First thing you need to know is that your users will either belong to Android or iOS platforms. 

Your App will depend on your idea, and your idea will decide your target audience. 

For Example, If my idea is to make a Food Delivery app, then I will have to create apps on both iOS and Android platforms because my target audience will be everyone. 

But if my idea is to create a Music app, then it will depend on the audience, whether my audience is using iOS / Android / Both platforms. 

If you’re targeting a global audience, Android will be your best choice. But if your audience is in the UK or US, Apple will be a better choice.

LogicRays Recommendation:

Depending in which country your user base belongs will help you make this decision. 

Go through your idea and observe, where you will be able to get more traffic on your application depending on your country you’re living in. 

#3 License Issue

License issues with Android and iOS are completely different. If you’re making an Application in iOS, it will cost you more than Android. 

iOS charges $99 per year to upload your application in the App Store. 

Where Android charges $30 for lifetime access to upload any Apps you want to upload in Google Playstore. 

iOS is very precise when it comes to choosing an application to upload in the Apple store because. iOS is very precise about the quality of application you’re uploading because Apple does not accept low-quality applications in their store. These conditions help them keep their standard high in the world. 

iOS goes pixel-to-pixel to check your Application. It is far more strict in App development, checks memory leaks, and Graphics of Application. 

In Android it is much easier for any application to get selected to be in Google Playstore. 

The Lifetime usage with affordable rates, make Android a much preferable choice for everyone because, not everyone can afford $99 every year unless their App runs successfully in iOS.

LogicRays Recommendation

Doesn’t matter if you’re a beginner or an Expert Mobile App Developer, Apple is much recommended because Apple is far more strict in accepting the app and renewing the license on a monthly basis. Thus, Apps in Apple are much more refined, strict, safe & secure. 

Android on the other hand comes with less price but less price means more users, more apps, more competition, and every type of apps. 

#4 Features

The feature of your app depends on the main idea behind creating this application and what your audience will need out of it. 

So, the main question for you is that “What features will you provide through your Mobile App?” Because Android is open source and it provides more flexibility compared to iOS. 

Building the features and functions that your audience wants is in your hand. 

Open source means Android has higher risk to pirate apps and malware. When you compare Apple with Android- Apple is more secure because of its closed nature. This is the reason why iOS has a bigger audience base in the enterprise market. 

It keeps the data of enterprise safe & secure.

LogicRays Recommendation:

For the enterprise market it is much more recommended to use Apple because it is much more secure & safe. Where Android is open-source, there are a good number of chances that a bug or malware can attack your application. 

Thus, if your application is for your personal purpose, then using Android for your App development is much preferred. 

#5 Integrated Development Environment (IDE)

Now when you write code for iOS, you use Xcode and when you write code for Android, you use Android studio. 

When you compare Xcode with Android Studio, Xcode is far more dominant than with the Android Studio. Since the things have now changed for Android Studio version 4.1, you don’t have to use third-party software like genymotion to speed up your performance of the emulator in the end right now. 

The default emulator is quite better than the previous version. 

On the other hand, Xcode is quite mature software because it has been through quite a lot of phases in every update. Thus, working on the Xcode is far more easier and less buggy, compared to the Android Studio. 

Also, the Android Studio has its own benefits like: arranging the things in layout is far more easier in the Android compared to Xcode because it comes with the linear layouts and compound layouts. 

At the end it is always your choice.

LogicRays Recommendation:

Apple has been dominating the market because of its ease of developing apps in Xcode. 

Since Android studio version 3 came out in October 2017, the issues related to bugs and lagginess got solved and the working with it became way more better than it used to be. 

Now that you’re getting a IDE at low rates, then why not choose it. 

#6 Monetization 

When you’re building an application, at some point you also hope to get your App monetized. 

Apple App store generates twice as much revenue compared to Google Playstore despite having half many downloads. 

Apple users are more likely to make in-app purchases and spend more on it. 

The likelihood of making purchases on iOS or Android determines how much money your app can make.

When you compare iOS users with Android users; Android users are less willing to pay for the apps. 

Thus, free apps with in-app-ads are more common in Android. 

Whereas, Apple App store brings in twice as much money as Google Play, despite the fact that there are half as many downloads. 

Apple users are more likely to make and spend money on in-app purchases.

LogicRays Recommendation:

Apple could be the best bet if you want to monetize your app without ads, freemium models by subscriptions, or in-app purchases. Here eCommerce Applications are no exception. 

In The End!

Android vs. iOS: Which Platform to Build Your App for First? 

Everything depends on where you are living, where your audience lives, what are their preferences, their feature requirements, license issue, and budget to determine where you should build a business app for iOS or Android first. 

If your product has minimum requirements, then Android can be the “Way to Go!” option for you. 

As well as, if you are looking forward to generating big bucks with your app or building an eCommerce app, iOS is the best option for you. 

Moreover, if your target is an emerging market or global market, depending on the region and features of your app, Android will be your best bet here. 

It doesn’t matter which platform you’re choosing.

Both platforms are on top and equally fantastic! 

We gave you perspective, now choice is yours!

With the help of LogicRays Technologies, you can now Hire Android Developer or Hire iOS Developer for creating the best business application you dreamt of. 

Why Python for a Startup is the Best Choice in 2021?

You’re having a great startup idea? Are you confused whether you should choose python for Startup idea or not? 

Here, with our points, you’ll get the right perspective about why you should choose python as a base platform for your Startup idea. As intelligent as it seems, your potential startup needs a pre classified critical approach. 

After the constant rise in 5 years, python ranks 3rd on the list of most loved technologies in the world and The average annual salary of a python developer in the US is $110,300 per year with the cash bonus of $5000 per year. 

Each and every startup has its own perspective and needs for development in terms of various functions, and features. For development, the platform you choose to build your idea should be minimal, versatile, simple, and easy to manage. 

Before you start, you need to determine the business goal behind this startup and how to deal with the challenges in the starting stage of startup. Ask yourself these questions and do a detailed research on it before you figure out which programming language you choose as a base platform. 

  • The base programming language for this startup will adapt with the new changes in MVP?
  • How much time will it consume to implement the idea in programming language? 
  • Will it simplify the work in critical products? 
  • How will you choose the best developer to build your tool?
  • Will this language handle web scraping, web automation, Artificial Intelligence, Big Data, and Machine Learning? 
  • The language you choose will help you scale the product?
  • Will it be able to handle both business intelligence and analytics?

Answering these questions for yourself is necessary to figure out MVP’s requirements and choose the best programming language for your startup idea. Here, Python is the answer to all your questions. 

We will start from the basics. 

What is Python?

Python is the top and highly used object-oriented, high-level, interpreted programming language. It is mainly used for Rapid Application Development, Scripting, and Editing the existing codes and components together. Minimal syntax and simplicity improves the readability of Python language, because of that, it reduces the cost of program maintenance. 

The following frameworks are recommended for python programming: Django, Flask, Web2Py, CherryPy, Pyramid, and TurboGears.

As a fully-optimized, open-source toolkit with great customizable architecture, it stimulates quick development with minimal coding. Many top applications in the world used Python as their base platform and brought huge differences in the world. These applications are: 

  • Instagram 
  • Disqus
  • Spotify
  • Youtube
  • Mozilla  

Even the top websites and applications use python as their base language. It is because of its simplicity, libraries, minimal code, and easy syntax. 

Now we will look at the reasons why Python for startups is the best choice for you? 

#1 Python for Web Scraping

In simple terms, Web scraping is extracting useful data from a website for our own purpose. Web scraping is performed with the aid of an algorithm or software that collects and processes a large amount of data from the internet. It doesn’t matter if you’re an engineer, data scientist, artist, or anybody who can analyze large datasets, this ability costs more and it is really useful if you have it. 

There are many applications given to web scraping, Some of them are:

Web scraping may be in use for a variety of purposes, including:

  • Lead Generation: Web scraping allows you to collect data of contact information from various sources that have really good and useful content. With this, you can find both personal information and information related to your business. 
  • Social Media Insights Management: With the help of web Scraping using python, you can predict trends in various social networks such as Twitter, Instagram, Pinterest, Facebook, TikTok, Snapchat, Reddit, and Tumblr. With this information, you can easily predict the plans for your social media page. 
  • Price Monitoring: Many companies use web scraping for services to analyze their competitors which helps them make a strategy for their own company. It also allows you to extract data from huge and popular retailers like Amazon, Flipkart, eBay, etc. 
  • Search Engine Optimization: With the help of scraping using the python algorithm, scraping organic search results will rapidly search your SEO competitors for any particular term. On the basis of that, you will be able to determine which keywords your competitors are targeting and decide the title tags.  

#2 Python for AI and ML

Machine Learning (ML) and Artificial Intelligence are the new black in developing IT industries. AI is used to handle the large work that cannot be done manually because of its intensified volume and intensity. According to Jean Francois Puget, from the Machine Learning Department of IBM, gave an opinion that Python is the most popular language for ML and AI.

To execute AI logics, you should make use of a programming language that is adaptable, accessible, and easy to understand. That is why Python is the best choice to implement AI and ML.

Advantage of Python that makes best fit for AI and ML. 

  • Access to various mind blowing structures and libraries
  • Minimal Coding
  • Environment friendly  
  • Extensive Network 
  • Basic and Predictable 

If you have an idea that requires Artificial intelligence as your base, you should use python for Artificial intelligence because it makes your work much easier and helpful at the same time. 

#3 Python Supports Data Science 

Python is one of the best languages used by Data Scientists around the world for various Projects and Applications. Python provides the best functionality to deal with scientific, mathematical, and statistics. It provides some of the best libraries that can deal with data science applications easily. Small syntax, adaptability, and quick response make it the most widely used software in this world.

The benefit of using Python for Data Science is; its libraries. Python provides a large base of libraries for doing mathematical and statistical analysis that helps data scientists to make their work easier and faster. Now analyzing the big data will become much easier with Python. 

When you are doing a startup in data science, choosing python to create your project will make your work 100 times easier. That’s why when you have a startup in the Data Science field, you should always choose Python for programming. 

#4 Python is Startup Specific

First thing about startups is that; in the beginning of their pace, every startup is broken. When you start, you’ll require a huge amount of bucks in your pocket to start. If you don’t have it, don’t panic because if you choose python for the development of a startup idea, it will cost you way less compared to the original price.

Second thing you need to know about startups is; it will not have a lot of time to convenience investors and partners. 

Thirdly, They will have to make their product work immediately in order to earn money out of it. 

If you use python as your base language when you start developing, then only these things will work. Use it to make an irresistible and the best product that astonishes everyone’s mind with your product. 

#5 Python Works on Complex Projects 

Projects such as creating a social network or a software with new functionalities are normally web-based. This web is handled by big data, be it social media, Netflix or Video streaming. This language deals with high-level complexities, which makes it easier to solve any problem in the development part. Python is ideal for web solutions. 

This language gives win-win when the word comes to scalability. For all the startups, it is very important to catch the ball of success in your hand while it lasts. If you make it to growing your business according to your choice with the success itself, it can spell out some good cash and benefits for future. 

#6 Small Team Works Best 

Python is not a tough language at all. It is very easy to learn and even a person from a non-engineering background can learn it easily. If you are looking forward to starting with developing your startup idea, you won’t need a team of developers to get the product in your hand. This gives startups a chance to try it, learn it and see it working. Thus, Keeping it simple in small will only benefit your  startup idea, because more is the number of people in a team, more will be opinions, and more confusion will be generated.

#7 Easy Investment 

Startups are nothing without investors and their funds. Your startup is based on investors because if your investors find your product unique, interesting, and useful, then only they will provide you the funding for your startup. Thus, it is important to show them what your product is all about. If you don’t have investors on your side, then the project will stay put. In 80% cases, proof of concept is just for convincing investors for investing in your startup. These proofs do not affect in any way considering the future.

Wrapping Up!

Now that you know, Startup is a kind of business that needs to go hit when you strike the ball to the player (between the audience). You have to fall into competition to win the race. Bring out the product that will help your audience in real life. The product you sell will decide the revenue of your business. 

Thus the whole web is big data, know about “How Python is Perfect Fit for Big Data?”. We hope that these points will help you understand why choosing Python is beneficial for your startup idea. So, did you like this article? Let us know in the comment section and if you have a good startup idea and you want help, Hire Python Developer at LogicRays Technology.

Why is Python a Best fit for Big Data?

“Python Language Is One Example. As We Noted Above. It Is Also Heavily Used For Mathematical And Scientific Papers. And Will Probably Dominate That Niche For Many Years Yet. – Eric S. Raymond”

Wherever you go, Python is everywhere! 

So, Why is Python a best fit for Big Data?

Python is designed in a way that is easy to write and read. Not being a complex language, gives it the benefit of more usage. According to Stack Overflow Trend, Python is acknowledged as the fastest-growing programming language.

Today, Python is taking over the world in its best way. Python takes the Top spot for the  fourth time as Most Popular Technologies in 2020. According to the responses of more than 60,000 developers around the world, Python is considered as the third “most loved” programming language. 

Python is an interpreted, open-source, general-purpose, and object-oriented programming language. creating the world’s top applications such as Instagram, Google, Spotify, Uber, Pinterest, Reddit, etc. 

Big data is the most precious commodity in this era. Someone said that “The Future of IT is Big Data”, well that is true, but how? 

Let’s start with the basics of “What exactly Big Data is?”. 

“Big Data is a huge cluster of data that is enormous in size and volume. 

The raw data comes with a large size and numerous complexity that no traditional tool can store, handle, and process it precisely. In short, Big data is data of large size. 

Big size companies possess a huge bundle of data, where processing, and analyzing it can take a pretty much large amount of time, and the results may not be precise. Selecting a programming language for Big Data is a project-specific task, that depends on its goal. It doesn’t matter what projects, Python is best fit for Big Data. 

But Why Python for Big Data? 

When people started combining Python and Big Data, the scenario of the marketplace changed and now, Big Data is much more efficient and easy to understand, because Python has made it easy to use and understandable for every developer. Python is in enormous demand among all Big Data Companies right now. 

Here, we will discuss why using python for Big Data is beneficial. 

#1 Open- Source

Open source is software in which the original code is released under a license. This code can be altered, modified, and enhanced according to developers needs. 

Python is an Open source programming language, thus, it supports multiple platforms. Python also supports environments like Linux, Windows, and MacOS. 

Instead of wasting time in technical terms of language, the simple, clean, and readable syntax helps Big Data experts to focus on case managing Big data easily. This is one of the main reasons to opt for Python for Big Data. 

Most Popular Programming Languages

#2 Simple and Minimal Coding 

Minimal codes in Python programming make it extensively used, compared to other languages that are available for programming. Python is known for its execution in a few lines of code. Moreover, it automatically provides help to associate and identify various data types. 

If you or someone has an idea, all you have to do is think and write 5-10 lines of code and there you go! Your program is ready to use. 

This programming language follows an indentation-based nesting i.e. structure instead of braces to structure any program in it. This language can bear a heavy and complicated task in just a click of time. That data computes in commodity machines, clouds, desktop, and laptop.

In the beginning, python was considered a slow language compared to its equivalents like Scala and Java. Now, the scenario has taken a turn of 360 since then. 

When Anaconda platform arrived in market, it came with a great speed to analyze the code. This is why Python for Big Data became the best option for everyone. 

Your Python project works best when you Hire Python Developer who can add the essence and benefits of python in your business.  

#3 Speed 

Python is highly popular for its high speed to analyze the code and for software development. The precision of Python to analyze code is perfect, because of that Python is the most appropriate choice for Big Data. It supports prototyping ideas that help to make the code run faster.

While doing so, Python also maintains the transparency between the process and the code. 

 After Anaconda entered the market, the whole scenario of working on python language changed. It came with a speed that made everything in it useful. Python programming makes sure that the code is transparent and readable.

Such speed made python more powerful, and Big Data can use that speed to make the development faster. 

#4 Libraries of Python for Big Data

Python offers a large set of standard libraries that includes corners like stings operations, internet protocols, operating system interface, and web service tool.

The standard library sets contain frequently used programming languages to make coding easier and smaller.

Python provides multiple useful libraries of your wish. This makes Python a famous programming language in the area of scientific computing. 

Big data, as the word suggests, it involves a huge amount of data analysis and computation. These libraries make the work easier for Big Data Analytics.

Python offers numerous pre-tested analytics libraries. Big Data Analytics uses these libraries filled with packages, such as:

  • Data Analysis: Inspecting, cleaning, modeling, and transforming any size of data (Large or Small) to discover some useful information for predicting the future of business on the basis of current information. 
  • Statistical Analysis: It is the process of collecting and analyzing the data, in order to analyze the trend and pattern.  
  • Machine Learning: As the name suggests, ML is programming a computer in such a way that it learns everything from different kinds of data on its own. Machine Learning uses python libraries like Numpy, Scikit-learn, Theano, TensorFlow, Keras, Pandas, PyTorch, and Matplotlib. 
  • Numerical Computing: Scientific computation is done by this. Scientific computing contains Scipy, Pandas, IPython, Natural language Toolkit, and Numeric python. 
  • Data Visualization: It gives many insights that data alone cannot provide. When you visualize the information, you bring your mind into the landscape that you explore with your eyes, like an information map in front of your eyes. Visualization libraries contain Matplotlib, Plotly, Seaborn, ggplot, and Altair. 
Library Features

 #5 Compatibility of Python with Hadoop

Hadoop’s framework is made using Java programming language. Hadoop programs also use C++ and Python. It means that even if the data architects don’t know anything about java, they can use python as an option. When you compare Java with Python, it is much easier to use python because of its small codes and high speed. 

Compared to other programming languages, Hadoop is more compatible with python. You can incorporate all the features into your business. For this, you will have to Hire Python Developer who is good with the skills. 

About Pydoop Package

Pydoop package is an interface of python to hadoop that gives you authority to write MapReduce applications and interact with HDFS applications in python. 

HDFS API let’s you write and read different information on directories, global file system properties without facing any problem. 

Pydoop provides MapReduce API for solving tough and complex problems with minimal programming. This API implements advanced data science concepts like ‘Record Reader’ and ‘Counter’, which makes Python the best fit for Big Data. 

#6 Data Processing Support 

Python comes with an inbuilt feature of supporting data processing. Data processing for unconventional and unstructured data. uses this feature. This is the main reason why big data analytics companies choose python over every option.

#7 Scope of Python for Big Data

Python is an object-oriented language that supports high-level data structures. It allows users to simplify all data operations. Python manages some of the data structures i.e. lists, dictionaries, tuples, sets, etc. Other than this, Python also supports scientific computing operations such as data frames, matrix operations, etc. 

These astonishing features of Python help to enhance the scope of language by enabling it to increase speed of data operations. This makes Python and Big Data the most charming and useful combination. That’s why python a best fit for Big Data.

Stack Overflow

Before We Apart

Now, You may have a clearer picture in front of you now about why Python is best fit for Big Data. To understand it more clearly, you will have to go deep into it and understand every single bit of it because Big Data is like a star in the universe, no matter how far you go, it will never reach its limit of learning. 

“Data is a precious thing and will last longer than the systems themselves.”- Tim Berners-Lee

Big Data technology is spreading across the world, people are learning and advancing themselves every day. It can be a very flinty task, but knowing why Python a best fit for Big Data will for sure help you make your way through learning Big data using Python.