Amazon Redshift Vs Azure Synapse Analytics: Difference Between Top Data Warehouses

By Veritis

Amazon Redshift Vs Azure Synapse Analytics: Difference Between Top Data Warehouses

In this modern-day generation, CIOs are soliciting IT professionals to provide an effective data platform that supports machine learning and data-driven innovation. Moreover, they also want to continue supporting data reports and traditional business intelligence tools. Successful ones find the solution for these needs without making trade-offs while appreciating the strengths of data warehouses.

A data warehouse is a central repository for a business to share and analyze the data to guide strategic decisions. To make productive data driven decisions, the data should be free of outliers, cropped results, and user mistakes. An organization can use data-driven evidence to choose which products to build, pursue growth initiatives, and add features. Essentially, the data warehouse can provide insight and intelligence that lead to competitive advantages and new opportunities.

While a plethora of data warehouses available in the current market, Amazon Redshift and Azure Synapse Analysis stand out as the top contenders. However, choosing the right vendor between Amazon Redshift and Azure Synapse is an arduous task as both offer a lot of advantages. In this blog, we shall guide you and help you choose the best provider for your platform.

Before delving into the major differences between the top two cloud platforms, we will introduce you to a data warehouse, Amazon Redshift, and Azure Synapse Analytics.

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What is a Data Warehouse?

What is a Data Warehouse?

As mentioned, A data warehouse (DWH) is a central reserve of information that can be extracted from operational sources and external data sources to produce business insights. It is typically used for data analysis, reporting, and business intelligence (BI). Data stored in the DWH is entirely different from data discovered in the operational environment.

DWH makes it easy to quickly analyze business data extracted from operational systems such as inventory management systems, point-of-sale systems, and marketing databases. Information gathered from transactional databases is hard enough to generate the data directly as it can gather through the data warehouse. For instance, an organization wants to know the total revenue produced by each salesperson for each product every month. Transactional databases may not generate this data, but the DWH can produce it.

Amazon Redshift – Cloud Data Warehouses

Amazon Redshift

Amazon Redshift is a data warehouse solution that enables business intelligence in the AWS cloud. Redshift allows customers to query petabytes of semi-structured and structured data using standard SQL queries. It is used for analysis and large-scale data storage, and Redshift frequently allows large-scale database migrations.

Users can start small with no commitments and scale up to petabytes or more. It allows them to operate their data to obtain new sights for their customers and business. Redshift is a fully managed solution that automates the most common administrative tasks associated with security, configuration, and maintaining backups, among others.

The Amazon Redshift data warehouse consists of computing resources called nodes in a cluster. Each cluster uses its Redshift engine with at least one database and performs data analytics queries. Nodes can be deactivated and activated based on the requirement so that enterprises can use from gigabytes to petabyte-level storage in minutes.

Amazon Redshift stores data securely, offering companies insights into nearly every aspect of their enterprise, from sales and marketing to website performance. AWS touts that Amazon Redshift is the world’s fastest cloud data warehouse service and has three times better price-performance than other vendors.


Amazon Redshift data warehouse is one of the cost-effective solutions that you need to pay only for what you consume. AWS charges USD 0.25 with no upfront and no commitment costs, and users can scale up to USD 250 per terabyte per year.

The cost of Amazon Redshift varies from one region to another. To put in perspective, the cost in US East (Ohio) would be.

Details Memory Addressable Storge Capacity vCPU I/O Cost
RA3 along with Redshift storage
ra3.xlplus 32 GiB 32TB RMS 4 0.65 GB/s USD 1.086/hour
ra3.4xlarge 96 GiB 128 TB RMS 12 2.00 GB/s USD 3.26/hour
ra3.16xlarge 384 GiB 128 TB RMS 48 8.00 GB/s USD 13.04/hour
Dense Compute
dc2.large 15 GiB 0.16TB SSD 2 0.60 GB/s USD 0.25/hour
dc2.8xlarge 244 GiB 2.56TB SSD 32 7.50 GB/s USD 4.80/hour

Useful Link: AWS vs Azure vs GCP: Cloud Cost Comparison

Azure Synapse Analytics – Cloud Data Warehouses

Azure Synapse Analytics

Azure Synapse Analytics is an unlimited information analysis service that combines the capabilities of enterprise data warehousing, big data analytics, ETL pipelines, analytics tools and services, visualization and dashboards, and data integration. It allows you to query data on your requirements, using either provisioned resources or serverless at scale.

Azure Synapse permits a single service for all workloads when managing, serving, and processing data for data protection and immediate business intelligence requirements. Features like data pipelines (powered by Azure data factory), data flow creation, data ingestion, data exploration, and data visualization are available in a single place. In addition, performance optimization and workload monitoring are part of the package.

Apache Spark pools are also available in Azure Synapse. This tool is one of the favourite tools for data scientists and data engineers, thanks to handling machine learning capabilities, compatibility and extensive data.

The design and architecture of the Azure Synapse data warehouse depend on multiple factors. A well-performing data warehouse should guarantee low latency, concurrency, data availability, and the ability to incorporate with other systems.


In terms of pricing, Azure Synapse offers a pay-as-you-go model. You pay only you consume for the services. However, prices can be higher than in the pre-purchasing model. Currently, it offers two versions – Azure Synapse Analytics which allows only data warehousing, and the next one is the new Azure Synapse Analytics pre-purchase plan.

In the current market, the pricing models for serverless and dedicated consumption are


The cost of a dedicated version varies from one region to another. To put in perspective, the cost in the central US would be.

DWU Service Level 1 year reserved 3 years reserved Pay as you go
100 DW100c USD 0.9513/hour USD 0.5285/hour USD 1.51/hour
500 DW500c USD 4.7563/hour USD 2.6425/hour USD 7.55/hour
1000 DW1000c USD 9.5126/hour USD 5.285/hour USD 15.10/hour
2000 DW 2000c USD 19.0252/hour USD 10.57/hour USD 30.20/hour
2500 DW2500c USD 23.7815/hour USD 13.2125/hour USD 37.75/hour
5000 DW5000c USD 47.563/hour USD 26.425/hour USD 75.50/hour
7500 DW7500c USD 71.3445/hour USD 39.6375/hour USD 113.25/hour
10000 DW10000c USD 95.126/hour USD 52.85/hour USD 151/hour
15000 DW15000c USD 142.689/hour USD 79.275/hour USD 226.50/hour
30000 DW30000c USD 285.378/hour USD 158.55/hour USD 453/hour


Azure Synapse serverless costs USD 5.65 TB of data processed and offers 1 TB of free queries per month until the last day of the year. You need to pay only for executed queries and data processed by each query.

Comparison between Amazon Redshift and Azure Synapse Analytics

Details Amazon Redshift Azure Synapse Analytics
Administration and Management Amazon requires AWS expertise to select the correct instance size and scale nodes manually Azure offers dedicated models and serverless
Integrations Ecosystem DMS, along with partners and data integration in the AWS marketplace Azure data factory supports integration
Ingestion of streaming data It doesn’t provide the built-in capability for ingestion of data streams Users can operate the Apache Spark streaming functionality to ingest streaming data
Data backup and recovery Available Available
Columnar Architecture Yes Yes
Massively parallel processing (MPP) Available Available
Database model Relational DBMS Relational DBMS
DB engine rankings Rank 31

Score 25.94

Rank 36

Score 20.66

Initial Release 2012 2016
Language implemented C C++
Supported programming languages It supports all languages related to ODBC/JDBC It supports Java, PHP, and C#
Pricing Amazon Redshift on-demand price related to on-cluster configuration. Users can buy reserved nodes at discount Azure Synapse Analytics on-demand price related to pre-purchase reserved storage at discount

Useful Link: Serverless Vs Containers: Comparison Between 2 Cloud Services

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Final Thoughts on Data Warehouses

Final Thoughts on Data Warehouses

Top MNC companies are running data warehouses, either cloud or on-premise, to gather valuable insights for business decisions. Most large enterprises operate hundreds of terabytes in data warehouses, while petabyte-sized data warehouses are rare, even in top multinational companies.

The two cloud providers have secured the top places in cloud computing, and they have cutthroat competition in the current market. Both Redshift and Azure Synapse Analytics are good enough for a business, depending on your specific requirements. They offer free trials to guide you in picking the right data warehouse vendor for your business.

Instead of picking between Amazon Redshift and Azure Synapse, why not opt for a multi-data warehouse strategy, which gets you numerous benefits for your business. However, adopting a multi-data warehouse strategy is a laborious process; this is why where organizations seek Vertis’s services.

Veritis, the Stevie Award Winner, is a next-generation global technology that helps companies reimagine their business and adapt them to the digital world.  Veritis offers holistic services to small, medium, and large-scale enterprises, including Fortune 500 firms with tailored, cost-effective, and efficient cloud solutions.

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FAQ’s – Amazon Redshift and Azure Synapse Analytics

A data warehouse (DWH) is a central reserve of information that can be extracted from external data sources and operational sources to produce business insights.

It uses business intelligence (BI), reporting, and data analysis. Data stored in the data warehouse is completely different from data revealed in the operational environment.

Amazon Redshift offers analytical tools and implementation services , and it also provides a flexible pricing scheme that starts at USD 0.25 per hour for a terabyte of data.

In contrast, Azure Synapse Analytics offers data pipeline, data ingestion, data exploration, data flow creation, and data visualization available in a single unit. In addition, it offers to pay as you go model.

Reviewers found both solutions equally simple to run when evaluating AWS Redshift and Azure Synapse Analytics. However, Amazon Redshift is easier to set up and operate, while Azure Synapse Analytics is easier to manage.

AWS Elastic Beanstalk is an Amazon Web Services (AWS) PaaS (Platform-as-a-Service) alternative to Azure App Service. It not only supports deployment on Rails servers, but it also supports other popular languages such as Java, PHP, and Go.

It allows you to effortlessly progress through the many stages of app development, providing the ideal atmosphere without the concern of constructing and maintaining the underlying infrastructure required for the development process.

A data warehouse is a central repository for a business to analyze and share the data to guide strategic decisions.

There are numerous cloud-based data warehousing tools, and the best among them are

  1. Amazon Redshift
  2. Microsoft Azure
  3. Micro Focus Vertica
  4. Snowflake
  5. Google BigQuery

Azure Analysis Services offers enterprise-grade BI semantic modeling capabilities with the cloud’s management, flexibility, and scale benefits. It is platform as a service (PaaS) approach that allows cloud-based enterprise data models.

In addition, Microsoft Azure Analysis Services is a new preview service that allows you to host semantic data models.

Amazon Redshift is a fully managed solution that automates the administrative tasks related to maintaining backups, security, configuration, and more. It allows customers to query petabytes of semi-structured and structured data using standard SQL queries.

Moreover, it is used to analyze large-scale data storage, and AWS Redshift usually permits large-scale database migrations.

An Amazon Redshift data warehouse is a relational database query and management system for businesses. It offers a customer to pick from six different database engines - Oracle database, PostgreSQL, MariaDB, MySQL, AWS Aurora, and SQL server.

AWS Redshift is a petabyte-scale data warehouse that makes analyzing all of your data with your existing business intelligence tools simple and cost-effective.

Amazon Redshift analyses semi-structured and structured data across data warehouses, data lakes, and operational databases with SQL leveraging machine learning and AWS designed technology to provide the best pricing performance at any scale.

Businesses may use Azure Synapse Analytics to manage their data lakes and data warehouses from a single location.

A few benefits of Azure Synapse Analytics are:

  1. Increased IT Productivity
  2. Better BI and Data visualization
  3. Accelerate Analytics and Reporting
  4. Limitless Scaling

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