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.
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.
"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."
"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."
"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."
"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."
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:
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:
Microsoft Azure Synapse Analytics Features
Microsoft Azure Synapse Analytics has many valuable key features, including:
Microsoft Azure Synapse Analytics Benefits
Some of the benefits of using Microsoft Azure Synapse Analytics include:
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."
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.
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.