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In this program, we are given an array of integers of even length as we know here we have to make groups of two. We have from that groups using elements of an array, we have to choose two groups among them in order to find the maximum difference between that two groups and we have to return that maximum difference which is going to see in the article below.

Introduction to Problem

In the given problem we have to find the Maximum difference between groups of size two. It means we have given an array of even length and we have to make groups of size two. As we have to return the maximum difference between the groups, we have to find one highest sum group and one lowest sum group and return the difference value of them.

We are given an array of size num,

Input: Num = 4 Array = {5, 1, 6, 7} Output: 7

Here groups formed will be the {5,1} and {6,7} i.e. 6 and 13 respectively and the difference between the highest sum and lowest sum is 13 – 6 is 7.

Example 2

Input: Num = 6 Array = {3, 1, 2, 4, 5, 6} Output: 8

Here groups formed will be the {1,2}, {3,4} and {5,6} i.e. 3, 7, and 11 respectively, and the difference between the highest sum and lowest sum is 11 – 3 is 8.

Approach 1: Brute force Approach

In this approach, we create every possible combination of groups and compare each set of combination differences between the group with the highest sum and the group with the lowest sum.

There would be n*(n-1)/2 such groupings in all (nC2).

Time Complexity: O(n^3), since it will require O(n^2) to construct groups and O(n) to check against each group.

Approach 2: Using the sort Function

In this approach, we first sort the array using the sort function as we know we needed the highest sum and the lowest sum of groups of two, so we added the first and second values of the sorted array the for lowest sum and last and second last value of a sorted array for the highest sum and then return the difference of that sum. Now let’s see an example of it.

Example

JavaScript program for finding the maximum difference between the groups of two using the sort function.

function calMaxDiff( array , num){ array.sort(); let highestVal = array[num - 1] + array[num - 2]; let lowestVal = array[0] + array [1]; return (Math.abs(highestVal - lowestVal)); } let num = 6; let array = [3, 1, 2, 4, 5, 6]; console.log("Maximum Difference: " + calMaxDiff( array, num )); Time and Space Complexity

The time complexity of the above code is O(NlogN) because here we use the sort function. Here N is a size of an array.

The space complexity of the above code is O(1).

Approach 3: By Finding a Maximum of Two and a Minimum of Two

In this approach, we have to find the first and second largest values of an array and find the first and second smallest values of an array.

Example

JavaScript program for finding the maximum difference between the groups of two.

The time complexity of the above code is O(N) because here we only traverse an array for finding the maximum and minimum values. Here N is a size of an array.

The space complexity of the above code is O(1).

Conclusion

In this article, we have discussed finding the maximum difference between groups of size two. Here we have discussed three approaches to solving the problem. First approach was with O(N^3) time complexity and the following one was with the O(N*log(N)), but the final approach was with time complexity of O(N).

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Golang Program To Calculate Difference Between Two Time Periods

In this tutorial, we will write a golang programs to calculate the difference between two time periods given in the following programs. To get the time difference between two time periods we can either use a library function or can create a separate user-defined function to achieve the results.

Method 1: Calculate the Difference between Two Time Periods using Internal Function

In this method, we will write a go language program to find the difference between time periods using pre-defined functions in go programming language.

Syntax func (t Time) Sub(u Time) Duration

The sub() function in go is used to get the difference between two dates. In this function the first two parameters i.e., t and u are date values and this function returns the difference between two values in hours, minutes, and seconds.

Algorithm

Step 1 − First, we need to import the fmt and time. The time package allows us to use other predefined packages like time.Date().

Step 2 − Start the main() function.

Step 3 − Initialize firstDate and secondDate variables by passing the dates and times in time.Date() function in the order of yy/mm/dd/hrs//min//sec

Step 4 − Find the difference between the given dates using Sub() function this function takes the second date as an argument and calculates the required difference.

Step 5 − Print the result on the screen in various formats.

Step 6 − We can print the years, days, months, weeks, hours, second, milliseconds, etc.

Example

Golang program to calculate the difference between two time periods using internal function

package main import ( "fmt" "time" ) func main() { firstDate := time.Date(2023, 4, 13, 3, 0, 0, 0, time.UTC) secondDate := time.Date(2010, 2, 12, 6, 0, 0, 0, time.UTC) difference := firstDate.Sub(secondDate) fmt.Println("The difference between dates", firstDate, "and", secondDate, "is: ") fmt.Printf("Years: %dn", int64(difference.Hours()/24/365)) fmt.Printf("Months: %dn", int64(difference.Hours()/24/30)) fmt.Printf("Weeks: %dn", int64(difference.Hours()/24/7)) fmt.Printf("Days: %dn", int64(difference.Hours()/24)) fmt.Printf("Hours: %.fn", difference.Hours()) fmt.Printf("Minutes: %.fn", difference.Minutes()) fmt.Printf("Seconds: %.fn", difference.Seconds()) fmt.Printf("Nanoseconds: %dn", difference.Nanoseconds()) } Output The difference between dates 2023-04-13 03:00:00 +0000 UTC and 2010-02-12 06:00:00 +0000 UTC is: Years: 12 Months: 148 Weeks: 634 Days: 4442 Hours: 106629 Minutes: 6397740 Seconds: 383864400 Nanoseconds: 383864400000000000 Method 2: Calculate the Difference between Two Time Periods using a User-Defined Function

In this method, we will create a different function to calculate the difference between the two provided dates. The function will take the two dates as arguments and return the respective result.

Algorithm

Step 1 − First, we need to import the fmt and time packages. The time package allows us to use other predefined functions like time.Date().

Step 2 − Create the leapYear() function to calculate the number of leap years between the two dates.

Step 3 − Also create the getDifference() to get the difference between date and time. getDifference() function returns the days, hours, minutes, and seconds.

Step 4 − Start the main() function.

Step 5 − Initialize date1 and date2 variables by passing the dates and times in time.Date() function in the order of yy/mm/dd/hrs//min//sec.

Step 6 − Swap the two dates if date1 occurs after date2.

Step 7 − Call the getDifference() by passing the two dates as arguments to the function.

Step 8 − Store the result obtained by the function in a different variable and print them on the screen in different formats using fmt.Println() function.

Example

Golang program to calculate the difference between two time periods using a user-defined function

package main import ( "fmt" "time" ) func leapYears(date time.Time) (leaps int) { y, m, _ := date.Date() if m <= 2 { y-- } leaps = y/4 + y/400 - y/100 return leaps } func getDifference(a, b time.Time) (days, hours, minutes, seconds int) { monthDays := [12]int{31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31} y1, m1, d1 := a.Date() y2, m2, d2 := b.Date() h1, min1, s1 := a.Clock() h2, min2, s2 := b.Clock() totalDays1 := y1*365 + d1 for i := 0; i < (int)(m1)-1; i++ { totalDays1 += monthDays[i] } totalDays1 += leapYears(a) totalDays2 := y2*365 + d2 for i := 0; i < (int)(m2)-1; i++ { totalDays2 += monthDays[i] } totalDays2 += leapYears(b) days = totalDays2 - totalDays1 hours = h2 - h1 minutes = min2 - min1 seconds = s2 - s1 if seconds < 0 { seconds += 60 minutes-- } if minutes < 0 { minutes += 60 hours-- } if hours < 0 { hours += 24 days-- } return days, hours, minutes, seconds } func main() { date1 := time.Date(2023, 4, 27, 23, 35, 0, 0, time.UTC) date2 := time.Date(2023, 5, 12, 12, 43, 23, 0, time.UTC) if date1.After(date2) { date1, date2 = date2, date1 } days, hours, minutes, seconds := getDifference(date1, date2) fmt.Println("The difference between dates", date1, "and", date2, "is: ") fmt.Printf("%v daysn%v hoursn%v minutesn%v seconds", days, hours, minutes, seconds) } Output The difference between dates 2023-05-12 12:43:23 +0000 UTC and 2023-04-27 23:35:00 +0000 UTC is: 716 days 10 hours 51 minutes 37 seconds Conclusion

We have successfully compiled and executed a go language program to get the difference between two time periods along with examples. In the first example, we used internal functions and in the second example, we used a user-defined function to obtain the results.

Difference Between Javascript And Angularjs

JavaScript is a scripting language that is used to generate dynamic HTML pages with interactive effects on a webpage that runs in the web browser of the client. On the other hand, Angular JS is a framework that is built on JavaScript and adds new functionalities to HTML. Its primary purpose is to facilitate the creation of dynamic and single-page web applications (SPAs).

In this article, we are going to highlight the differences between Angular JS and JavaScript. Let’s start with a basic understanding of JavaScript and AngularJS.

What is JavaScript?

JavaScript is a simple programming language that is most frequently utilised as a part of webpages. JavaScript implementations on webpages make it possible for client−side scripts to interact with the user and produce dynamic websites. It is a type of programming language that is interpreted and can handle features that are object−oriented.

The fundamental JavaScript programming language was given a standard form by the ECMA−262 Specification.

JavaScript is interpreted and therefore very lightweight.

It is designed for the purpose of developing apps that focus on networks.

JavaScript complements and is fully incorporated with HTML. It is free to use on several operating systems.

JavaScript Development Tools

Many different manufacturers have developed quite helpful JavaScript editing tools in order to make our lives easier. For example, Microsoft FrontPage is a widely used HTML editor. Web developers have access to a variety of JavaScript tools inside FrontPage, which may aid them in the process of creating dynamic websites.

Utilization of JavaScript

Creating interactive webpages often requires the usage of JavaScript. Its primary applications are:

Client-side validation,

Dynamic drop-down menus,

Including the date and the time,

Putting up new windows and dialogue boxes as they appear (like an alert dialogue box, confirm dialogue box, and prompt dialogue box),

Including things like clocks, etc.

Here’s a simple JavaScript code:

document

write

(

“This text in to JavaScript”

)

;

What is AngularJS?

The AngularJS Framework is an extremely strong version of JavaScript. Single Page Application (SPA) projects use Angular JS. It enhances the responsiveness of HTML DOM to user actions and adds new properties that increase HTML DOM’s capabilities.

AngularJS is a free and open−source software framework that is used by thousands of developers all over the globe. It is distributed with the Apache licence version 2.0 attached to it.

If one already has a fundamental understanding of JavaScript, then learning AngularJS is a breeze.

General Features of Angular JS

The following is a list of the general properties that AngularJS possesses:

With the help of the AngularJS framework, you can make Rich Internet Applications (RIAs) that work well.

Developers have the option, thanks to AngularJS, of writing client−side apps in JavaScript in a manner that is cleanly Model View Controller (MVC).

Applications that are created in AngularJS are compatible with a wide variety of browsers. AngularJS handles JavaScript code in a manner that is automatically appropriate for each browser.

AngularJS is a web development framework that is open source, does not cost anything to use, and is used by thousands of developers all over the globe. It is licenced under version 2.0 of the Apache General Public License.

Benefits of Using AngularJS

The benefits of using AngularJS are as follows:

AngularJS makes it possible to make Single Page Applications that are very well organised and easy to keep up.

It adds the possibility of data binding to HTML. As a result, it provides the user with an experience that is both rich and responsive.

AngularJS code is unit testable.

Dependency injection and separation of concerns are two concepts that are used by AngularJS.

AngularJS offers reusable components.

Overall, AngularJS allows developers to accomplish greater functionality with fewer lines of code.

Drawbacks of Using AngularJS

Even though there are lots of benefits that come with AngularJS, there are still some concerns that need to be addressed.

Applications created with AngularJS are not secure since the framework only supports JavaScript, which makes them insecure. To keep an application safe, authentication and authorization have to be done on the server.

Not degradable: If a user of your application disables JavaScript, then nothing other than the default page will be shown.

Difference between JavaScript and AngularJS

The following table highlights the major differences between JavaScript and AngularJS:

Key JavaScript AngularJS

Definition It is an object−oriented scripting language that is used in the process of application development, specifically for mobile and dynamic web platforms.

It is an open−source framework that may be used to create dynamic web applications as well as massive single−page web apps.

Programmed It uses the C and C++ programming languages to write its interpreters. The code behind AngularJS is written in JavaScript.

Syntax Its syntax is far more difficult to understand than that of Angular JS. Its syntax is simple and easy.

Filters It doesn’t support the filters. It is possible to use filters with it.

Concept The principle of dynamic typing serves as its foundation. Angular JS is an application−building framework that is predicated on the MVC architectural pattern.

Dependency injection The dependency injection mechanism is not supported by it. AngularJS supports both data binding as well as dependency injection.

Conclusion

The creation of web apps may be accomplished using either of these two web technologies. Both JavaScript and AngularJS are free and open−source programming languages. AngularJS is an open-source framework based on the MVC approach.

JavaScript is a kind of computer language that may be used to create websites. It can make websites more interactive. It is possible to alter the content on websites in order to check user reaction at the browser end. As a result, it is possible to influence user activity by integrating dynamic content such as drag−and−drop components, sliders, and a great many other things. It is the basis for all JavaScript technologies and is considered to be one of the three basic technologies that make up the World Wide Web.

Javascript Program For Find K Pairs With Smallest Sums In Two Arrays

In this article, we will first find all the pairs that can be made with two arrays. Then, according to the value of k, we will display the pairs with the smallest sums in two arrays.

Here, we will first use the brute-force method to solve the problem, then we will use various methods to optimize the same. So, let’s get started with the problem statement and some examples.

Problem Statement

We are given with the two arrays arr1[] and arr2[] sorted in ascending order, and a nonnegative integer k, the objective is to find k pairs with the smallest sum such that one element of each pair belongs to arr1[] and the other element belongs to arr2[]. Let’s see some examples to clear our concepts.

Example

Input

arr1[] = [2, 3, 6, 7, 9] arr2[] = [1, 4, 8, 10] k = 1

Output

[2, 1]

Explanation − The first smallest sum pair is [2, 1] which is obtained from [2, 1], [3, 1], [6, 1], [7, 1], [9, 1], [2, 4], [3, 4], [6, 4], [7, 4], [9, 4], [2, 8], [3, 8], [6, 8], [7, 8], [9, 8], [2, 10], [3, 10], [6, 10], [7, 10], [9, 10].

Example

Input

arr1[] = {2, 4, 6, 8} arr2[] = {1, 3, 5, 7} k = 4

Output

[2, 1], [2, 3], [4, 1], [4, 3]

Explanation − The first 4 pairs are returned from the sequence [2, 1], [2, 3], [4, 1], [4, 3], [6, 1], [6, 3], [8, 1], [6, 5], [8, 3], [8, 5], [6, 7], [8, 7]

Now let’s see various ways to solve the above problem.

Method 1: Brute Force

The brute force approach to solve this problem involves generating all possible pairs from the given two arrays and then selecting the k pairs with the smallest sums. this approach has a time complexity of O(n^2 log n), which is not efficient for large input sizes.

Algorithm

Initialize an empty list called ‘pairs‘ to store all possible pairs.

Loop through each element ‘a‘ in the first array ‘arr1‘.

Loop through each element ‘b‘ in the second array ‘arr2‘.

Append a new pair ‘[a, b]‘ and its sum ‘a + b‘ to the ‘pairs’ list.

Sort the ‘pairs‘ list in ascending order based on the sum of each pair.

Extract the first ‘k‘ pairs from the sorted ‘pairs‘ list.

Return the ‘k‘ pairs as the result.

Example

let arr1 = [1, 7, 11]; let arr2 = [2, 4, 6]; const kInput = document.getElementById(‘k’); const output = document.getElementById(‘output’); const arr1El = document.getElementById(‘arr1’); const arr2El = document.getElementById(‘arr2’);

function displayArrays() { arr1El.textContent = `arr1 = [${arr1.join(‘, ‘)}]`; arr2El.textContent = `arr2 = [${arr2.join(‘, ‘)}]`; }

function findKPairs() { const k = parseInt(kInput.value); let pairs = [];

for (let i = 0; i < arr1.length; i++) { for (let j = 0; j < arr2.length; j++) { pairs.push([arr1[i], arr2[j], arr1[i] + arr2[j]]); } }

output.innerHTML = result; }

displayArrays();

Method 2: Two Pointer Approach

The two pointer approach requires initializing two pointers, one for each array, to the array’s beginning. Finally, using these pointers, we iterate through the arrays, comparing the sums of the elements at the current pointer positions and storing the pairings with the k least sums. We just shift the pointer corresponding to the smaller element ahead at each step to make this process as efficient as possible.

We can observe from this two-pointer approach that the above problem has an O(k log k) time complexity, which is substantially faster than the O(n2) time complexity required by a brute force approach.

Algorithm

Initialize pointers i and j to the beginning of arrays nums1 and nums2, respectively.

Initialize an empty list pair to store the k pairs with smallest sums.

While both pointers i and j are within the bounds of their respective arrays and the length of pairs is less than k −

Calculate the sum of the elements at the current pointer positions, and add this pair to pairs.

If nums1[i] is less than or equal to nums2[j], move pointer i forward by 1. Otherwise, move pointer j forward by 1.

Return pairs.

Example

const nums1 = [1, 2, 4, 5, 6]; const nums2 = [1, 3, 4, 7, 8]; const k = 3;

const inputDiv = document.getElementById(“input”); const pairs = findKPairsWithSmallestSums(nums1, nums2, k);

const outputDiv = document.getElementById(“output”); for (let i = 0; i < pairs.length; i++) { }

Conclusion

In this tutorial, we have discussed writing a program to find k pairs with the smallest sums in two arrays. We used brute force method first then optimized it with a two pointer approach.

Javascript Program For Shortest Un

The problem statement requires finding the shortest un-ordered subarray in an array of integers. In other words, we need to identify the smallest subarray in which the elements are not sorted in ascending or descending order. This problem can be solved through various approaches, but in this article, we will discuss a simple and efficient solution using JavaScript.

So first we will start by defining what an un-ordered Subarray is, then understand the problem statement in detail and then proceed to explain the step-by-step solution using examples and code snippets. By the end of this article, you will have a clear understanding of how to solve this problem in JavaScript. So let’s get started!

What is an Un-Ordered Subarray?

An un-ordered subarray is a contiguous subarray of an array in which the elements are not in ascending or descending order. In other words, the elements in the subarray are not arranged in a sequence that is either increasing or decreasing.

For example: [1, 2, 3, 5, 4, 6, 7] is an un-ordered subarray.

Problem Statement

Given an array of integers, we need to find the shortest un-ordered subarray. In other words, we need to identify the smallest subarray in which the elements are not sorted in ascending or descending order.

For example, let’s consider the following array: const arr = [1, 2, 5, 4, 3, 6, 7]

In this case, the subarray [5, 4, 3] is the shortest un-ordered subarray.

Now let’s understand the algorithm for solving this problem and then we move to the implementation of this algorithm using JavaScript.

Algorithm for Shortest Un-Ordered Subarray

Input − An array of n integers

Output − The length of the shortest subarray that is un-ordered

STEP 1 − Initialize start = 0, end = n-1

STEP 2 − Traverse the array from left to right and find the first element that is greater than its right neighbour. Set its index to start.

STEP 3 − Traverse the array from right to left and find the first element that is smaller than its left neighbour. Set its index to end.

STEP 4 − Find the minimum and maximum element in the subarray starting from start to end.

STEP 5 − Traverse the array from 0 to start-1 and find the index of the first element that is greater than the minimum element found in step 4. Set its index to the left.

STEP 6 − Traverse the array from end+1 to n-1 and find the index of the first element that is smaller than the maximum element found in step 4. Set its index to the right.

STEP 7 − The length of the shortest un-ordered subarray is (right – left + 1).

Example

In the below example, we first find the starting and ending indices of the un-ordered subarray by iterating through the array from the beginning and end respectively. We then find the minimum and maximum elements in the subarray, and then we find the left and right indices of the subarray by iterating through the array from the beginning and end respectively.

Finally, we return the length of the shortest un-ordered subarray by subtracting the right index from the left index and adding 1.

We discussed every nuance of how we can execute the Shortest Un-Ordered Subarray problem using JavaScript. We hope with this article, one can easily find and fix issues related to un-ordered subarrays in their code.

Difference Between Hadoop Vs Redshift

Difference between Hadoop and Redshift

Hadoop is an open-source framework developed by Apache Software Foundation with its main benefits of scalability, reliability, and distributed computing. Data processing, Storage, Access, and Security are several types of features available in the Hadoop Ecosystem. HDFS has a high throughput which means being able to handle large amounts of data with parallel processing capability. Redshift is a cloud hosting web service developed by the Amazon Web Services unit within chúng tôi Inc., Out of the existing services provided by Amazon. It is used to design a large-scale data warehouse in the cloud. Redshift is a petabyte-scale data warehouse service that is fully managed and cost-effective to operate on large datasets.

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Hadoop, Data Science, Statistics & others

Hadoop HDFS has high fault tolerance capability and was designed to run on low-cost hardware systems. Hadoop can handle a minimum type size of TeraBytes to GigaBytes of files within its system. HDFS is master-slave architecture consisting of Name Nodes and Data Nodes where the Name Node contains metadata and Data Node contains real data to be processed or operated.

RedShift uses different data loading techniques such as BI (Business Intelligence) reporting, analytical tools, and data mining. Redshift provides a console to create and manage Amazon Redshift clusters. The core component of the Redshift Data Warehouse is a cluster.

Image Source: Apache.org

RedShift Architecture:

Head to Head Comparison between Hadoop and Redshift (Infographics):

Below is the top 10 comparisons between Hadoop and Redshift are as follows.

Key Differences Between Hadoop vs Redshift

Below is the Key Differences between Hadoop vs Redshift are as Follows

1. The Hadoop HDFS (Hadoop Distributed File System) Architecture is having Name Nodes and Data Nodes, whereas Redshift has Leader Node and Compute Nodes where Compute nodes will be partitioned as Slices.

2. Hadoop provides a command-line interface to interact with file systems whereas RedShift has a Management console to interact with Amazon storage services such as S3, DynamoDB etc.,

3. The database operations are to be configured by developers. Redshift automates the database operations by parsing the execution plans.

5. In terms of Hadoop architectural design, network, storage, security, and performance have been considered primary elements whereas in Redshift these elements can be easily and flexibly configured using Amazon cloud management console.

6. Hadoop is a File System architecture based on Java Application Programming Interfaces (API) whereas Redshift is based on a Relational model Database Management System (RDBMS).

8. Most of the existing companies are still using Hadoop whereas new customers are choosing RedShift.

9. In terms of, performance Hadoop always lacks behind and Redshift always wins over in the case of query execution on large volumes of data.

10. Hadoop uses Map Reduce programming model for running jobs. Amazon Redshift uses Amazon’s Elastic Map Reduce.

11. Hadoop uses Map Reduce programming model for running jobs. Amazon Redshift uses Amazon’s Elastic Map Reduce.

12. Hadoop is preferable to run batch jobs daily that becomes cheaper whereas Redshift comes out cheaper in the case of Online Analytical Processing (OLAP) technology that exists behind many Business Intelligence tools.

14. In terms of Data Loading too, Hadoop has been behind Redshift in terms of hours taken by the system to load data from the storage into its file processing system.

15. Hadoop can be used for low-cost storage, data archiving, data lakes, data warehousing and data analytics whereas Redshift comes under Data warehouse capabilities causing to limiting the multi-purpose usage.

16. Hadoop platform provides support to various external vendors and its own Apache projects such as Storm, Spark, Kafka, Solr, etc., and on the other side Redshift has limited integration support with its only Amazon products

Hadoop vs Redshift Comparison Table

BASIS FOR

COMPARISON

HADOOP REDSHIFT

Availability Open Source Framework by Apache Projects Priced Services provided by Amazon

Implementation Provided by Hortonworks and Cloudera providers etc., Developed and provided by Amazon

Performance Hadoop MapReduce jobs are slower Redshift performs more faster than Hadoop cluster

Scalability Limitations in scalability Easily be down/upsized as per requirement

Pricing Costs $ 200 per month to run queries The price depends on the region of the server and is cheaper than Hadoop

Eg: $20/month

Speed Faster but slower compared to Redshift 10 times faster than Hadoop

Query Speed Takes 1491 seconds to run 1.2TB of data 155 seconds to run 1.2TB data

Data Integration Flexible with the local file system and any database Can load data from Amazon S3 or DynamoDB only

Data Format All data formats are supported Strict in data formats such as CSV file formats

Ease of Use Complex and trickier to handle administration activities Automated backup and data warehouse administration

Conclusion

The final statement to conclude the big winner in this comparison is Redshift that wins in terms of ease of operations, maintenance, and productivity whereas Hadoop lacks in terms of performance scalability and the services cost with the only benefit of easy integration with third-party tools and products. Redshift has been recently evolving with tremendous growth and acceptance by many customers and clients due to its high availability and less cost of operations compared to Hadoop makes it more and more popular. But, till now most of the existing Fortune 1000 companies have been using Hadoop platforms in its architectures to manage the customer data.

In most the cases RedShift has been the best choice to consider for the business purposes by any client or customer in order to handle the large and sensitive data of any financial institutions or public information with more data integrity and security.