Amazon uses a lot of adjectives to describe its cloud data warehouse: AWS Redshift is "fast," "simple" and "cost-effective." 

It's also popular. GE, McDonald's, Bosch, Coca Cola, and countless other brands, ranging from startups to Fortune 500 companies, have added Redshift to their tech stacks. 

But why is AWS Redshift used? And why is it the world's No.1 cloud data warehouse?

Below, learn more about what Redshift does, how it does it, and why it could be a great fit for your organization. 

Table of Contents is an ETL solution that moves data from disparate sources into AWS Redshift. This process requires no code, so you can transfer data without hiring a data engineering team. Start your seven-day free trial with to learn more. 

Read more:'s Guide to Amazon Redshift

What Is a Data Warehouse?

Before learning why people use Redshift, you need to understand the concept of a data warehouse. It's a type of data management system that stores data from various sources in one central hub so users can generate business intelligence (BI) from that data. BI is the process of analyzing business analytics to make better organizational decisions. It combines metrics, data mining tools, data visualization processes, and other strategies. 

Why is this important?

Because business analytics matter.

Organizations need as much information as possible so they can improve performance and increase sales. Data analytics provides them with that information, making it easier to interpret the complex data sets that exist in different systems. 

Data is all very well and good, but enterprises need a way to understand that data. Otherwise, it's useless.

And that's where BI is critical. 

A data warehouse isn't the only way to amass data for analytics, but it's the most effective. That's because it's capable of storing large amounts of data in various formats from different systems. The best warehouses run in the cloud, so users can keep as many data sets as they like without worrying about storage limitations. Consider that the average enterprise manages an incredible 347.56 TB of data and you can see why so many companies use a cloud data warehouse to store their information. 

Using a data warehouse brings other benefits. As governments crackdown on companies that violate data governance legislation, such as GDPR and CCPA, it's easier to manage sensitive data in one place rather than use several systems. 

Why Is AWS Redshift Used as a Data Warehouse?

So many organizations choose Redshift because of its reputation. It's arguably the fastest warehouse in the world — Amazon claims Redshift runs ten times faster than any other enterprise cloud data warehouse — and it offers lots of security with a data center and network architecture that meets international data protection standards. Other security features include encryption, sign-in credentials, access management and cluster security groups. 

There are other advantages.

Redshift utilizes a warehouse model where nodes exist in a cluster, with each cluster running its own engine alongside a database. So it's easy to scale the platform based on your data requirements. Plus, some organizations will benefit from Redshift's pay-as-you-go pricing model that charges users for the amount of data used. 

Redshift currently has an average user score of 4.2 out of 5 on the software review website, making it one of the most popular warehouses on the market. 

Here are what some users think:

  • "It takes data from different sources and puts them together in Redshift for our analytics team to diagnose. It is fairly quick and easy to set up and we can add nodes fairly quickly to expand our data needs."
  • "The robustness of Redshift is by far the best across all cloud-based data warehouses and it also has a great UI."
  • "It is fast. We can use it concurrently and we can use SQL over it so we don't have to learn a new language. The Redshift dashboard allows us to cancel requests that take too many resources." 

Read more: Amazon Redshift SecurETL to Your Data Warehouse

What Can't You Use Redshift For?

While Redshift scores points for its speed, security, and overall performance, there are some things it just can't do. One of those things is complex data transfers

Many businesses get excited when they hear about this powerful data warehouse. However, few know how difficult it can be to move data to Redshift. The platform can load data from sources such as Amazon S3 and Amazon EMR using a method called massively parallel processing, but it doesn't support parallel loading. That means you can't load data from a transactional database, customer relationship management (CRM) system, enterprise resource planning (ERP) system, or other sources.

Not directly in Redshift, anyway. 

For those kinds of transfers, you need an ETL solution.

ETL stands for Extract, Transform and Load. It's a three-step process that moves data from almost any location to Redshift so you can perform analytics on that data. You can implement ETL manually or use a digital tool to do it for you. Here's how these tools work:

  1. ETL solutions extract data from a source such as a relational database, transactional database, or another data store automatically with little human intervention. 
  2. Then they transform the data into a format for analytics.
  3. Then they load the data to a data warehouse such as Redshift.

This process requires no code (or very little code) and makes it simple to move data from one location to another. 

Read more: Allowing Access to My Redshift Cluster

How Helps is an ETL solution that transfers data sets to Redshift so you can store information in one place and generate valuable BI analytics. The platform has a native connector that moves data to this warehouse with no code required.

It's not just Redshift. 

You can use one of the platform's no-code connectors for data transfers to warehouses such as Snowflake, Google Big Query, and IBM Db2. has a drag-and-drop point-and-click interface, so it's easy to use. Plus, it defines dependencies between tasks and allows for simple workflow creation. is the no-code ETL platform that transports data to AWS Redshift for storage and analytics. Start your seven-day free trial with to learn more or find more answers to the question "Why is AWS Redshift Used?" here