We performed a comparison between Microsoft Azure Synapse Analytics and Snowflake based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Based on the parameters we compared, Snowflake had a better user rating regarding ease of deployment and pricing. Both softwares had the same rating when it came to service and support. In terms of features, Microsoft Azure Synapse Analytics users felt the software had security issues and didn’t feel it was very intuitive. In contrast, users of Snowflake felt the UI needed improvement.
"The most advantageous aspect of Microsoft Azure Synapse Analytics is its simplified data transformation process compared to traditional databases. This makes data cleansing and transformation more manageable and straightforward, which we appreciate. It is much easier to build as well."
"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."
"I have been working with Microsoft, and they have been very helpful."
"I like how Microsoft Azure Synapse Analytics integrates with other Microsoft solutions."
"Very interactive and provides flexibility."
"The main advantage of using this solution is its ability to scale and handle very large amounts of data, in the petabyte range."
"Overall deployment and integration is pretty fast."
"Can capture all the transactional data throughout a company."
"It is a highly scalable solution. There is no limit on storage or computing."
"It is a very good platform. It can handle structured and semi-structured data, and it can be used for your data warehouse or data lake. It can load and deal with any data that you have. It can extract data from an on-premises database or a website and make it available in the cloud. It has very fast implementation and integration as compared to other solutions. There is no need for the DBA to manage or do the day-to-day DBA tasks, which is one of the greatest things about it."
"The product is quite fast."
"The syntax is advanced which reduces the time to write code."
"It is a cloud solution with many useful features. It has the data science capability. It can transform data and prepare data for a data science project with scalability."
"It's user-friendly. It's SQL-driven. The fact that business can also go to this application and query because they know SQL is the biggest factor."
"The querying speed is fast."
"Scaling is a big plus point of Snowflake."
"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."
"Right now, we are really struggling with the performance. it's not as good as we had hoped."
"Integration with other vendors has limitations and could be improved."
"It would be beneficial to take the top vendors and identify some kind of straightforward action to work with them. Instead of having to employ a separate vendor tool to be able to move this, it would be nice to be able to go through Microsoft."
"It's a complicated product."
"I would like to see them provide the ingestion of images."
"One area that could be improved is the schema management."
"Scaling this solution up and down is not quick and easy. This could be improved. The pricing of this solution could also be improved."
"In a future release we would like to have a link which would allow us to connect to an external database and create certain views in your own database. This is because it is becoming hard for us to compare the data between multiple sources."
"Snowflake has to improve their spatial parts since it doesn't have much in terms of geo-spatial queries."
"They need to improve its ETL functionality so that Snowflake becomes an ETL product. Snowpipe can do some pipelines and data ingestion, but as compare to Talend, these functionalities are limited. The ETL feature is not good enough. Therefore, Snowflake can only be used as a database. You can't use it as an ETL tool, which is a limitation. We have spoken to the vendor, and they said they are working on it, but I'm not sure when they will bring it to production."
"There are a lot of features that they need to come up with. A lot of functions are missing in Snowflake, so we have to find a workaround for those. For example, OUTER APPLY is a basic function in SQL Server, but it is not there in Snowflake. So, you have to write complex code for it."
"These aren't as crucial, but there are common errors sometimes where the database is down, or a table is nullified and a new table is added and you are not given access to that. With those errors, you don't have permissions."
"Snowflake has support for stored procedures, but it is not that powerful."
"There are three things that came to my notice. I am not very sure whether they have already done it. The first one is very specific to the virtual data warehouse. Snowflake might want to offer industry-specific models for the data warehouse. Snowflake is a very strong product with credit. For a typical retail industry, such as the pharma industry, if it can get into the functional space as well, it will be a big shot in their arm. The second thing is related to the migration from other data warehouses to Snowflake. They can make the migration a little bit more seamless and easy. It should be compatible, well-structured, and well-governed. Many enterprises have huge impetus and urgency to move to Snowflake from their existing data warehouse, so, naturally, this is an area that is critical. The third thing is related to the capability of dealing with relational and dimensional structures. It is not that friendly with relational structures. Snowflake is more friendly with the dimensional structure or the data masks, which is characteristic of a Kimball model. It is very difficult to be savvy and friendly with both structures because these structures are different and address different kinds of needs. One is manipulation-heavy, and the other one is read-heavy or analysis-heavy. One is for heavy or frequent changes and amendments, and the other one is for frequent reads. One is flat, and the other one is distributed. There are fundamental differences between these two structures. If I were to consider Snowflake as a silver bullet, it should be equally savvy on both ends, which I don't think is the case. Maybe the product has grown and scaled up from where it was."
"The solution should offer an on-premises version also. We have some requirements where we would prefer to use it as a template."
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Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 38 reviews while Snowflake is ranked 1st in Cloud Data Warehouse with 40 reviews. Microsoft Azure Synapse Analytics is rated 8.0, while Snowflake is rated 8.4. 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". On the other hand, the top reviewer of Snowflake writes "Easy to set up with great cloning and time travel". Microsoft Azure Synapse Analytics is most compared with Azure Data Factory, SAP BW4HANA, Amazon Redshift, Oracle Autonomous Data Warehouse and Teradata, whereas Snowflake is most compared with BigQuery, Azure Data Factory, Teradata, Vertica and Amazon EMR. See our Microsoft Azure Synapse Analytics vs. Snowflake report.
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