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 features most valuable are the simplicity, how easy it is to create a dashboard from different information systems."
"Scaling this solution is easy and the uptime is okay."
"Technical support is okay in terms of the help they provide."
"The pricing seems to be quite fair."
"The most valuable feature is performance gains."
"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 speed is great and the architecture is excellent."
"The ability to scale out services on-demand and scale them down when they are not required is most valuable. You are in control of your expenditures, and you are also in control of the horsepower that you need. That's a major advantage."
"The solution is very easy to use."
"Its performance is a big advantage. When you run a query, its performance is very good. The inbound and outbound share features are also very useful for sharing a particular database. By using these features, you can allow others to access the Snowflake database and query it, which is another advantage of this solution. It has good security, and we can easily integrate it. We can connect it with multiple source systems."
"My company wanted to have all our data in one single place and this what we use Snowflake for. Snowflake also allows us to build connectors to different data sources."
"The technical support on offer is excellent."
"The solution's computing time is less."
"Data Science capabilities are the most valuable feature."
"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."
"The speed of data loading and being able to quickly create the environment are most valuable."
"With respect to what needs to be improved, concurrent connectivity has some limitations."
"I am pretty sure that there are areas that need improvement but I just can think of them off the top of my head."
"One area that could be improved is the schema management."
"They should provide a less expensive version with a smaller setup for small businesses. Currently, its price is quite high for entry-level or small businesses. In terms of integration, new connectors are always welcomed."
"The need to improve a little bit in terms of user-friendliness."
"We encountered data processing and transformation issues while working with Apache Spark languages for the product."
"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."
"The initial setup process needs improvement. When you're moving to the cloud it takes a bit of time. It would be great if they could implement something that would make it faster."
"These days, they are pushing users towards the GUI or graphical version. However, I am more familiar with the classic version. I'd like to continue to work with it using the older approach."
"There are some challenges with loading unstructured data and integrating some message queues or brokers. In one project, we had a problem connecting to one of the message queues and we had to take a different route altogether on Microsoft Azure."
"I would like to see more transparency in data processing, ATLs, and compute areas - which should give more comfort to the end users."
"I don't know about GCP, if they have connected for GCP. If they don't, they should allow for it."
"The cost of the solution could be reduced."
"The design of the product is easily misunderstood."
"It needs a bit more rigor and governance, which is something you don't get with newer tools. This makes it less enterprise scalable. Its governance and structure can be enhanced, which would really be valuable. I would like to see some kind of prebuilt functionality in terms of having almost like a pre-built data warehouse. A functionality for generating automated kind of pieces would be good."
"The cost is a bit high."
More Microsoft Azure Synapse Analytics Pricing and Cost Advice →
Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 85 reviews while Snowflake is ranked 1st in Cloud Data Warehouse with 92 reviews. Microsoft Azure Synapse Analytics is rated 8.0, while Snowflake is rated 8.4. The top reviewer of Microsoft Azure Synapse Analytics writes "No competitors provide the entire solution to one place ". On the other hand, the top reviewer of Snowflake writes "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". Microsoft Azure Synapse Analytics is most compared with Azure Data Factory, SAP BW4HANA, Amazon Redshift, Teradata and Oracle Autonomous Data Warehouse, whereas Snowflake is most compared with BigQuery, Azure Data Factory, Teradata, Vertica and Oracle Exadata. See our Microsoft Azure Synapse Analytics vs. Snowflake report.
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