Amazon Redshift vs Microsoft Azure Synapse Analytics comparison

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Comparison Buyer's Guide
Executive Summary
Updated on Apr 10, 2022

We performed a comparison between Amazon Redshift and Microsoft Azure Synapse Analytics based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.

  • Ease of Deployment: Amazon Redshift reviewers agree that its installation is a straightforward process. Some Microsoft Azure Synapse Analytics users say that its initial setup is straightforward, while others say it is complex.
  • Features: Users of both products are happy with their stability and scalability. Amazon Redshift users say that it is user-friendly and has good machine learning features. Several users mention that it can slow down when performing multiple operations simultaneously.

    Microsoft Azure Synapse Analytics users say it is simple to use, fast, and flexible. A few users mention that its performance needs to improve.
  • Pricing: Most reviewers of both solutions say that they are fairly priced.
  • ROI: Amazon Redshift reviewers do not mention ROI. Microsoft Azure Synapse Analytics reviewers report seeing an ROI.
  • Service and Support: Most reviewers of both solutions report being satisfied with the level of support they receive.

Comparison Results: Amazon Redshift comes out on top in this comparison. It is easy to use and performs well. In addition Amazon Redshift is easier to set up than Microsoft Azure Synapse Analytics.

To learn more, read our detailed Amazon Redshift vs. Microsoft Azure Synapse Analytics Report (Updated: November 2022).
653,522 professionals have used our research since 2012.
Q&A Highlights
Question: How does Amazon Redshift compare with Microsoft Azure Synapse Analytics?
Answer: Amazon Redshift is very fast, has a very good response time, and is very user-friendly. The initial setup is very straightforward. This solution can merge and integrate well with many different databases. It scales very easily and has a good cost-benefit ratio. It is very powerful and performs well. The data processing is very fast and can do analytics on the fly. Amazon Redshift should have more cloud-native tools that integrate with it as Microsoft does with the Azure ecosystem. There is some missing functionality that can make Redshift difficult to work in. If you are analyzing a lot of data, the load performance-wise can be very low. Microsoft Azure Synapse Analytics can handle large amounts of data - in the petabyte range. You can scale up and down as much as you want. It has a pay-as-you-go protocol, so you only pay for what you use. The speed is very good and the architecture is excellent. You are in control of what you need, which is a huge advantage. Microsoft Azure Synapse Analytics can be a very complicated product to use. The setup can be very complex. We had some issues with dashboard reporting - we found there were bugs in the platform when dealing with specific types of queries. This solution did not meet the necessary security protocols for some of our clients. Conclusion Both of these solutions are very stable, scalable, and flexible. Each of these products has their own unique ecosystems that are very competitive with each other, making them both great solutions to use. Although they are very similar, there are some features and functionalities that make them unique and attractive depending on the type of enterprise you operate. We are a smaller enterprise and overall our team felt based on ease of use, support, and where we are headed, we have started to migrate everything over to an AWS ecosystem and chose Amazon Redshift. It is the solution our clients liked best as well.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
"Redshift's Excel features are handy. Redshift spectrum allows you to directly query the data on an Excel sheet. Now, SQL Server also allows this, but Redshift has many more features.""This service can merge and integrate well with all databases.""Amazon Redshift is very fast. It has really good response times. It's very user-friendly.""Setup is easy. It's a fast solution with machine learning features, good integration, and a good API.""Changing from local servers to the cloud is very easy. It's so nice not to have to worry about physical servers.""For the on-premises version of Amazon Redshift, we need to start from scratch. However, with the cloud version whenever you want to deploy, you can scale up, and down, and it has a data warehousing capability. Redshift has many features.""Has a very user-friendly SQL editor and it's very easy to use the connectors.""The most valuable features of Amazon Redshift are that its fast and efficient. We have lots of TBs of data and it's very fast."

More Amazon Redshift Pros →

"The initial setup is very simple.""We've had a good experience with technical support in general.""Synapse Analytics' best feature is its ability to process large files.""I think the most valuable component is that pipelines are built into it and then the feature that you can mirror a cosmos BB for analytics.""The most valuable features of Microsoft Azure Synapse Analytics are how easy and quick it is to set up the linked services.""The solution can scale.""Its seamless integration with Azure services is most valuable. If somebody wants to use all Azure services, it is the best solution.""The solution operates like a typical SQL Server environment so there is no alienation in terms of technical knowledge."

More Microsoft Azure Synapse Analytics Pros →

"Improvement could be made in the area of streaming data.""There is some missing functionality and sometimes it's so difficult to work in. We need to convert these functionalities using VACUUM inside Amazon Redshift and then it causes some complexity.""Planting is the primary key enforcement that should be improved.""Redshift's GUI could be more user-friendly. It's easier to perform queries and all that stuff in Azure Synapse Analytics.""Amazon Redshift could improve the user interface support.""The technical support should be better in terms of their knowledge, and they should be more customer-friendly.""Amazon should provide more cloud-native tools that can integrate with Redshift like Microsoft's development tools for Azure.""The refreshment rate of data reaching Redshift from other sources should be faster."

More Amazon Redshift Cons →

"The need to improve a little bit in terms of user-friendliness.""The major challenge that we're seeing with Azure Synapse is around security concerns. The way it is working right now, it has Managed VNet by Microsoft option, similar to the implementation of Azure Databricks, which may pose a concern for financial institutions. For managed environments, the banks have very strict policies around data being onboarded to those environments. For some confidential applications, the banks have the policy to encrypt it with their own key, so it is sort of like Bring Your Own Key, but it is not possible to manage the resources with Microsoft or Databricks, which is probably the major challenge with Azure Synapse. There should be more compatibility with SQL Server. It should be easier to migrate solutions between different environments because right now, it is not really competitive. It is not like you can go and install SQL Database in some other environment. You will have to go through some migration projects, which probably is one of the major showstoppers for any bank. When they consider Synapse, they not only consider the investment in the actual service; they also consider the cost of the migration process. When you scale out or scale down your system, it becomes unavailable for a few minutes. Because it is a data warehouse environment, it is not such a huge deal, but it would be great if they can improve it so that the platform is available during the change of configuration.""Integration with other products is an area that can be improved.""An area for improvement in Microsoft Azure Synapse Analytics is its user interface. You can use it for analytical purposes, but its platform should be a little bit more user-friendly. Another small point for improvement in Microsoft Azure Synapse Analytics is its stability. It's good currently, but it could still be improved. Microsoft is combining different tools and technologies into one solution, so in the future, I'm expecting to see even more improvement in Microsoft Azure Synapse Analytics. An additional feature I'd like to see in the next version of Microsoft Azure Synapse Analytics is the drag-and-drop feature. If you're doing some integrations where you can write Scala or you have SPARK programming or SQL, or you're combining different programming, the process should be seamless, and you should be able to drag and drop in Microsoft Azure Synapse Analytics. When doing reporting in the solution, you should also be able to drag and drop. There should be connectors available and a drag-and-drop feature available in the user interface of Microsoft Azure Synapse Analytics, so you won't have to worry about how all processes would work together. You need to be able to drag and drop even from the backend, and having this feature will make the solution more user-friendly.""The filing can be improved.""In the future, Microsoft Azure Synapse Analytics could improve the performance, there are other solutions that are better, such as Databricks.""Synapse Analytics is generally stable, but its performance can be slow when performing very large datasets.""The product could be more feature-rich."

More Microsoft Azure Synapse Analytics Cons →

Pricing and Cost Advice
  • "The price of the solution is reasonable. According to the RA3 cluster particularly, it provides 128 GB of storage with only four nodes. If you can manage your computations processes with the help of materialized views and proper queries. I think the IP clusters are very useful and overall fair for the price."
  • "This solution implements the pay-as-you-use model, so no license. Pricing could be cheaper."
  • "The price of Amazon Redshift is reasonable because it depends on the usage that you use and for DWH for the long term."
  • "Amazon Redshift is an expensive solution. Larger organizations can afford this solution, but smaller businesses would struggle to afford it."
  • "It's pay per use. You can have multiple models."
  • "The cost is comparable to Snowflake."
  • "The product is cheap considering what it provides; I rate it five out of five for affordability."
  • More Amazon Redshift Pricing and Cost Advice →

  • "The cost of the licensing depends on the size of the warehouse, where the cost of storage is approximately $130 USD per terabyte."
  • "This is a cost-effective product."
  • "Because it's cloud the cost is a different convention and the licensing costs are not the same."
  • "It's very difficult to price unless you know exactly how the customer is using it."
  • "We normally pay between $300 and $500 per month, which is quite expensive for how much we actually use it, performance- and usage-wise. They have a cheap version and an expensive version, and our usage usually falls in the middle ground, which makes it not as cost-effective as it could be."
  • "The solution is subscription-based. You can also pay to use the product as you go."
  • "It requires a less expensive version because currently, not every customer is able to buy it. If it could have a smaller setup that doesn't require so many resources, it would be helpful, and we would be able to use it in more cases. We are a small country, and most of our customers are quite small businesses."
  • "It goes by the usage, and there are some limits. Synapse goes by particular pricing, and it is expensive. Both Azure Synapse Analytics and Snowflake are pretty expensive. They don't have standard pricing. They deal with each customer differently."
  • More Microsoft Azure Synapse Analytics Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:Amazon Redshift is very fast, has a very good response time, and is very user-friendly. The initial setup is very straightforward. This solution can merge and integrate well with many different… more »
    Top Answer: We have found Machine Learning use cases are very nice.
    Top Answer:The initial setup is very smooth and took us about six months to deploy. The cost is comparable to Snowflake.
    Top Answer:Traditional ETL would usually use a dedicated database (or even database server) where you'll load & transform your raw data before ingesting it into the final destination. This would allow checking… more »
    Top Answer:The most valuable feature of Microsoft Azure Synapse Analytics is the pipeline that is the ETL tool. It's very well designed and is overall very good. We usually don't use the ETL tool in Databricks… more »
    Top Answer:You have to be very careful with one specific service inside Microsoft Azure Synapse Analytics which is called the Sequel Data Warehouse Dedicated. It is very reliable and performs well, but it's… more »
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    Also Known As
    Azure Synapse Analytics, Microsoft Azure SQL Data Warehouse, Microsoft Azure SQL DW, Azure SQL Data Warehouse, MS Azure Synapse Analytics
    Learn More

    What is Amazon Redshift?

    Amazon Redshift is a fully administered, petabyte-scale cloud-based data warehouse service. Users are able to begin with a minimal amount of gigabytes of data and can easily scale up to a petabyte or more as needed. This will enable them to utilize their own data to develop new intuitions on how to improve business processes and client relations.

    Initially, users start to develop a data warehouse by initiating what is called an Amazon Redshift cluster or a set of nodes. Once the cluster has been provisioned, users can seamlessly upload data sets, and then begin to perform data analysis queries. Amazon Redshift delivers super-fast query performance, regardless of size, utilizing the exact SQL-based tools and BI applications that most users are already working with today.

    The Amazon Redshift service performs all of the work of setting up, operating, and scaling a data warehouse. These tasks include provisioning capacity, monitoring and backing up the cluster, and applying patches and upgrades to the Amazon Redshift engine.

    Amazon Redshift Functionalities

    Amazon Redshift has many valuable key functionalities. Some of its most useful functionalities include:

    • Cluster administration: The Amazon Redshift cluster is a group of nodes that contains a leader node and one (or more) compute node(s). The compute nodes needed are dependent on the data size, amount of queries needed, and the query execution functionality desired.
    • Cluster snapshots: Snapshots are backups of a cluster from an exact point in time. Amazon Redshift offers two types of snapshots: manual and automated. Amazon will store these snapshots internally in the Amazon Simple Storage Service (Amazon S3) utilizing an SSL connection. Whenever a Snapshot restore is needed, Amazon Redshift will create a new cluster and will import data from the snapshot as directed. 
    • Cluster access: Amazon Redshift provides several intuitive features to help define connectivity rules, encrypt data and connections, and control the overall access of your cluster.
    • IAM credentials and AWS accounts: The Amazon Redshift cluster is only accessible by the AWS account that created the cluster. This automatically secures the cluster and keeps it safe. Inside the AWS account, users access the AWS Identity and IAM protocol to create additional user accounts and manage permissions, granting specified users the desired access needed to control cluster performance.
    • Encryption: Users have the option to choose to encrypt the clusters for additional added security once the cluster is provisioned. When encryption is enabled, Amazon Redshift will store all the data in user-created tables in a secure encrypted format. To manage Amazon Redshift encryption keys, users will access AWS Key Management Service (AWS KMS).

    Reviews from Real Users

    Redshift's versioning and data security are the two most critical features. When migrating into the cloud, it's vital to secure the data. The encryption and security are there.” - Kundan A., Senior Consultant at Dynamic Elements AS

    “With the cloud version whenever you want to deploy, you can scale up, and down, and it has a data warehousing capability. Redshift has many features. They have enriched and elaborate documentation that is helpful.”- Aishwarya K., Solution Architect at Capgemini

    Microsoft Azure Synapse Analytics is an end-to-end analytics solution that successfully combines analytical services to merge big data analytics and enterprise data warehouses into a single unified platform. The solution can run intelligent distributed queries among nodes, and provides the ability to query both relational and non-relational data.

    Microsoft Azure Synapse Analytics is built with these 4 components:

    1. Synapse SQL
    2. Spark
    3. Synapse Pipeline
    4. Studio

    Microsoft Azure Synapse Analytics Features

    Microsoft Azure Synapse Analytics has many valuable key features, including:

    • Cloud Data Service: WIth Microsoft Azure Synapse Analytics you can operate services (data analytics, machine learning, data warehousing, dashboarding, etc.) in a single workspace via the cloud.

    • Structured and unstructured data: Microsoft Azure Synapse Analytics supports both structured and unstructured data and allows you to manage relational and non-relational data - unlike data warehouses and lakes that tend to store them respectively.

    • Effective data storage: Microsoft Azure Synapse Analytics offers next-level data storage with high availability and different tiers.

    • Responsive data engine: Microsoft Azure Synapse Analytics uses Massive Parallel Processing (MPP) and is designed to handle large volumes of data and analytical workloads efficiently without any problems.

    • Several scripting languages: The solution provides language compatibility and supports different programming languages, such as Python, Java, Spark SQL, and Scala.

    • Query optimization: Microsoft Azure Synapse Analytics works well to facilitate limitless concurrency and performance optimization. It also simplifies workload management.

    Microsoft Azure Synapse Analytics Benefits

    Some of the benefits of using Microsoft Azure Synapse Analytics include:

    • Database templates: Microsoft Azure Synapse Analytics offers industry-specific database templates that make it easy to combine and shape data.

    • Better business insights: With Microsoft Azure Synapse Analytics you can expand discovery of insights from all your data and apply machine learning models to all your intelligent apps.

    • Reduce project development time: Microsoft Azure Synapse Analytics makes it possible to have a unified experience for developing end-to-end analytics, which reduces project development time significantly.

    • Eliminate data barriers: By using Microsoft Azure Synapse Analytics, you can perform analytics on operational and business apps data without data movement.

    • Advanced security: Microsoft Azure Synapse Analytics provides both advanced security and privacy features to ensure data protection.

    • Machine Learning: Microsoft Azure Synapse Analytics integrates Azure Machine Learning, Azure Cognitive Services, and Power BI.

    Reviews from Real Users

    Below are some reviews and helpful feedback written by Microsoft Azure Synapse Analytics users who are currently using the solution.

    PeerSpot user Jael S., who is an Information Architect at Systems Analysis & Design Engineering, comments on her experience using the product, saying that it is “Scalable, intuitive, facilitates compliance and keeps your data secure”. She also says "We also like governance. It looks at what the requirements are for the company to identify the best way to ensure compliance is met when you move to the cloud."

    Michel T., CHTO at Timp-iT, mentions that "the features most valuable are the simplicity, how easy it is to create a dashboard from different information systems."

    A Senior Teradata Consultant at a tech services company says, "Microsoft provides both the platform and the data center, so you don't have to look for a cloud vendor. It saves you from having to deal with two vendors for the same task."

    Learn more about Amazon Redshift
    Learn more about Microsoft Azure Synapse Analytics
    Sample Customers
    Liberty Mutual Insurance, 4Cite Marketing, BrandVerity, DNA Plc, Sirocco Systems, Gainsight, Blue 449
    Toshiba, Carnival, LG Electronics,, Adobe, 
    Top Industries
    Computer Software Company26%
    Comms Service Provider21%
    Logistics Company11%
    Computer Software Company20%
    Financial Services Firm13%
    Comms Service Provider9%
    Manufacturing Company6%
    Computer Software Company24%
    Comms Service Provider12%
    Financial Services Firm12%
    Manufacturing Company9%
    Computer Software Company20%
    Comms Service Provider11%
    Financial Services Firm9%
    Manufacturing Company6%
    Company Size
    Small Business30%
    Midsize Enterprise28%
    Large Enterprise42%
    Small Business18%
    Midsize Enterprise11%
    Large Enterprise71%
    Small Business29%
    Midsize Enterprise21%
    Large Enterprise50%
    Small Business18%
    Midsize Enterprise14%
    Large Enterprise68%
    Buyer's Guide
    Amazon Redshift vs. Microsoft Azure Synapse Analytics
    November 2022
    Find out what your peers are saying about Amazon Redshift vs. Microsoft Azure Synapse Analytics and other solutions. Updated: November 2022.
    653,522 professionals have used our research since 2012.

    Amazon Redshift is ranked 4th in Cloud Data Warehouse with 15 reviews while Microsoft Azure Synapse Analytics is ranked 3rd in Cloud Data Warehouse with 47 reviews. Amazon Redshift is rated 8.0, while Microsoft Azure Synapse Analytics is rated 7.8. The top reviewer of Amazon Redshift writes "Helps consolidate all of an organization's data into a single unified data platform". On the other hand, the top reviewer of Microsoft Azure Synapse Analytics writes "Multifeatured, has better performance over other solutions, and lets users manage structured and unstructured information, but the platform needs to be more user-friendly". Amazon Redshift is most compared with Snowflake, AWS Lake Formation, Oracle Exadata, Vertica and Teradata, whereas Microsoft Azure Synapse Analytics is most compared with Snowflake, Azure Data Factory, SAP BW4HANA, Apache Hadoop and AWS Lake Formation. See our Amazon Redshift vs. Microsoft Azure Synapse Analytics report.

    See our list of best Cloud Data Warehouse vendors and best Data Warehouse vendors.

    We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.