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.
"The most valuable feature of Amazon Redshift is its ability to handle really large sets of data."
"Setup is easy. It's a fast solution with machine learning features, good integration, and a good API."
"The product offers good support for the data lake."
"The ability to reload data multiple times at different times."
"It's scalable because it's on the cloud."
"Easy to build out our snowflake design and load data."
"The most valuable features are that it's easy to set up and easy to connect the many tools that connect to it."
"The processing of data is very fast."
"The integrated workspace in Microsoft Azure Synapse Analytics where everything comes together, such as Power BI and Data Factory, is very good. Additionally, the ability to do dedicated SQL pooling is a benefit."
"The platform has multiple valuable use cases. They include performance, compatibility, flexibility, and cost."
"The setup is pretty simple."
"The product is very user friendly."
"The most valuable features are the flexibility and that it's easy to use as an end-user compared to AWS."
"I like the keynotes and their simplicity. Like other Microsoft products, Microsoft Azure Synapse Analytics is simple to understand and use."
"The most valuable aspect of this Microsoft Azure Synapse Analytics is its consolidation of technical support from Microsoft, and its ability to securely host large quantities of data within the cloud environment. The overall ability to manage and maintain Big Data within the cloud provides a heightened level of efficiency, reliability, and support from Microsoft. This results in a superior user experience and an increased level of value for the end user."
"It is a highly stable solution and it's easy to use."
"They should provide a better way to work with interim data in a structured way than to store it in parquet files locally."
"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."
"There are physically too many pipelines for a company of this size to maintain. For a data scientist, it's very difficult to learn the data in all of these different environments."
"Pricing is one of the things that it could improve. It should be more competitive."
"In the solution, user-based access is quite hard. In general, certain permissions are difficult to manage."
"In our experiments, the handling of unstructured data was not very smooth."
"I would like to improve the pricing and the simplicity of using this solution."
"The technical support should be better in terms of their knowledge, and they should be more customer-friendly."
"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."
"The support and price could improve."
"Microsoft Azure Synapse Analytics can improve by adding more flexibility to the reports. Having more visible structures based on the area, region and country would be beneficial."
"We encountered data processing and transformation issues while working with Apache Spark languages for the product."
"Synapse Analytics needs to develop an automation framework because now you have to build a cache yourself. You have to build a pipeline in WhereScape, which does end-to-end pipeline automation well. Microsoft should come up with a framework to save people time. If they developed a tool like WhereScape, it would dramatically reduce development time."
"They should automate some of the features. There are some things, such as the creation of external tables, that you have to do manually. They should be automated."
"The linked services can be improved. We can create dynamic linked services to access a lot of databases but only those of the same type. For example, I can use the same linked services to access 11 SQL databases. However, if I have 11 SQL databases and five Oracle databases, I need two dynamic linked services. I cannot do it with only one linked service. The UI also needs to be improved. When I have used Azure Synapse for programming with PySpark, Scala, or .NET, for example, the UI has been unstable. If I open two notebooks for programming, one notebook will queue the session of the other."
"The product could be more feature-rich."
More Microsoft Azure Synapse Analytics Pricing and Cost Advice →
Amazon Redshift is ranked 4th in Cloud Data Warehouse with 58 reviews while Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 85 reviews. Amazon Redshift is rated 7.8, while Microsoft Azure Synapse Analytics is rated 7.8. The top reviewer of Amazon Redshift writes "Provides one place where we can store data, and allows us to easily connect to other services with AWS". On the other hand, the top reviewer of Microsoft Azure Synapse Analytics writes "No competitors provide the entire solution to one place ". Amazon Redshift is most compared with AWS Lake Formation, Snowflake, Vertica, Teradata and Oracle Exadata, whereas Microsoft Azure Synapse Analytics is most compared with Azure Data Factory, SAP BW4HANA, Snowflake, Oracle Autonomous Data Warehouse and Apache Hadoop. See our Amazon Redshift vs. Microsoft Azure Synapse Analytics report.
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