Amazon Redshift Vs Microsoft Azure: Which Data Warehouse Is Better?

Data Warehouse

Every company wants to manage its business based on data.  And cloud technology is changing the global business landscape. At the same time, a number of related areas have emerged. If you are an advanced analytics company, you need to be familiar with the concept of a data warehouse. Cloud data warehouses play an important role in storing business data from internal and external sources. There are many options to choose from, and some data warehouses offer more than just data storage.

Among the most popular storage options, we have selected two industry favorites to compare, Redshift vs Azure. In this article, we analyze their features and objectively compare them to see which solution might be more beneficial for your business. A comparative analysis between them has performed. Redshift is Amazon’s cloud data warehouse and Azure SQL Data Warehouse is Microsoft’s cloud data warehouse. A brief overview of these two are discussed below.

Features of the Microsoft Azure Data Warehouse

Azure SQL Data Warehouse meets all requirements with its non-shared architecture. The ability to store in different locations allows large amounts of data to be processed in parallel. If you are new to Azure data warehouse and to fully understand it, an Azure training course by experts can help. The course will teach you about virtual networks, Azure engines and much more.


Azure Blob Storage distributes data in a transparent manner. It can contain huge amounts of unstructured data. It provides reliable backup and restores data in a short time.

Compute Nodes

When a query is received, it is stored and processed by the compute nodes. Parallel processing of queries is also done by multiple compute nodes. When processing is complete, the results are returned to the control node.

Control Nodes

The control nodes coordinate all activities, from data transfer to the computation of parallel applications. To this end, each application is redesigned to run in parallel on multiple compute nodes.

Why Microsoft Azure Is Important


It is highly scalable as Azure Data Warehouse allows you to separate the compute and storage components. It is possible to add and remove resources during query execution.

Disaster Recovery

It’s almost impossible to predict when and how your web application will fain. So, it is important to always prepare for the worst. And the Disaster Recovery Tools built into Microsoft Azure can help.

Simple Structure

It’s important to structure your data into a three-dimensional model, as this is what users choose in the first place. Data analysts are recommended to use a data warehouse to ensure consistent results and to save time, money and effort.

Amazon Redshift Data Warehouse Features

The Redshift platform is known for its focus on continuous innovation, but its architecture has made it one of the most powerful cloud storage solutions. Here are three features that differentiate Redshift from other data warehouse.


Amazon Redshift enables users to accelerate data collection and gain valuable business insights in minutes by integrating selected partner solutions with the Redshift console. It also allows users to combine different data sets and analyze them together to get actionable insights.

Fault Tolerance

Data availability and storage resilience are of paramount importance to all users. Fault tolerance is the ability of a system to function even if some components fail. With Redshift, clusters are being monitored round the clock. When a node or cluster goes down, Redshift would automatically back up the data and move it to a new node.

Scalable Requirements

Amazon Redshift provides the flexibility to run console queries, library or business intelligence tool. It’s Query Editor provides a powerful interface to execute SQL queries in clusters, and display queries on compute nodes.

Reasons To Choose Redshift Data Warehouse

Pulling data from a variety of sources that are easily accessible in the Redshift solutions, businesses can quickly gain a deeper understanding of the data. Data from different internal business applications, including log files, can be transformed and transferred into Redshift worksheets, giving businesses deeper insight into the data available.


Amazon Redshift offers access control, data encryption and virtual private cloud to protect your data. It cares about cloud security and offers automatic backup to multiple locations.


Amazon Redshift integrates well with third-party applications and tools using Redshift API. With it you can automate the integration process, easily create data workflows, and enable on-demand data integration for everyone in your organization.


Redshift shifts data horizontally between old and new nodes in a cluster, so that clusters remain available for read-only operations. Adding nodes with a single click does not interrupt continuous data availability. Because Redshift can scale resources as needed, organizations can achieve scalability at the optimum level.

Redshift Vs Azure: Which Is Better?

Amazon Redshift and Microsoft Azure data warehouse have a lot to offer. Azure SQL Data Warehouse leads the way in certain areas, such as scalability and data center decoupling. Redshift is a leader in security because it can be stored in VPC.

Frankly, the answer depends on your specific needs. Microsoft Azure Synapse Analytics and Amazon Redshift are high performance data warehouses. Both offers a free trial so you can decide which solution is best for your business.

Still not sure which one is right for you? Contact a trusted data warehouse consulting service provider with years of experience in the industry now.

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