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.
"It is quite simple to use and there are no issues with creating the tables."
"In terms of valuable features, I like the columnar storage that Redshift provides. The storage is one of the key features that we're looking for. Also, the data updates and the latency between the data-refreshes."
"The most valuable feature is that the solution is fully embedded in the AWS stack."
"I find the most valuable features to be the MPP style of processing, which mostly all of the data warehouses provide. The ability to integrate all other AWS services, such as NSS and S3, with little effort is very helpful. The service is well maintained, there are update patches frequently."
"It's scalable because it's on the cloud."
"You can copy JSON to the column and have it analyzed using simple functions."
"The most valuable feature is the scalability, as it grows according to our needs."
"Setup is easy. It's a fast solution with machine learning features, good integration, and a good API."
"It is a fantastic product; we are satisfied with its features and performance."
"I have been working with Microsoft, and they have been very helpful."
"The most valuable features of Microsoft Azure Synapse Analytics are how easy and quick it is to set up the linked services."
"The main advantage of using this solution is its ability to scale and handle very large amounts of data, in the petabyte range."
"Synapse Analytics' best feature is its ability to process large files."
"One of the most valuable features of this solution is its ability to integrate well with other services offered by Azure."
"We use Azure Synapse Analytics in many different areas and industries, so I like that you can administrate and create pipelines for difference sources of data and later integrate and deploy it to other internal areas, such as separate dashboards for financials, and so on."
"It's quite quick for querying, even with large datasets, and it's scalable. It's also flexible to use, so it's easy to update and get data quickly without wasting time."
"The refreshment rate of data reaching Redshift from other sources should be faster."
"In terms of improvement, I believe Amazon Redshift could work on reducing its costs, as they tend to increase significantly. Additionally, there are occasional issues with nodes going down, which can be problematic."
"We are using third-party tools to integrate Amazon Redshift, they should create their own interface on their own for it to be easily connected on the AWS itself."
"This solution lacks integration with non-AWS sources."
"The OLAP slide and dice features need to be improved."
"The initial deployment was complex."
"The product must become a bit more serverless."
"The explain panel in the Redshift database could be better."
"Integration with other products is an area that can be improved."
"It needs strong support for social media, internet data, and native support for NoSQL."
"Unfortunately, we have had some issues with the dashboard reporting. Sometimes, the data for specific periods would just appear blank on the dashboard. To investigate this, we worked with a Microsoft incident agent and it turned out to be a result of bugs in the platform when dealing with specific types of queries in Azure Data Factory."
"Microsoft Azure Synapse Analytics can improve by increasing the size of the files that we can load on the platform. We have some files that are too large to be loaded and it would be a benefit to us if the limit was increased. Additionally, the way we use the tool for generating reports can be made better. They should add some drag-and-drop rules without the need of programming these rules using some programming language. It would be helpful if we did not need someone that was technically advanced to be able to do it with, such as someone with no IT background. Having a reporting tool without code would be great."
"Indicating what areas need improvement in this solution is a difficult question because the organizations that I am working for are really new in this area. However, an even better more simple interface, or perhaps an extension of a connector app store solution, would be helpful."
"Synapse makes it easy to integrate and onboard data from other Microsoft and Azure sources. The interface is familiar because we were using Azure Data Factory before Synapse. It made the transition even easier because the Synapse interface is exactly the same."
"Microsoft should develop an interface to make it easier to shift from on-premise to the cloud."
"If I'm looking for something good in the cloud, I would want it to have better standard connectors."
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, Teradata, Vertica 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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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.
