We performed a comparison between Microsoft Parallel Data Warehouse and Snowflake based on real PeerSpot user reviews.
Find out in this report how the two Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The solution's integration is good."
"Data collection and reporting are valuable features of the solution."
"It is not a pricey product compared to other data warehouse solutions."
"Microsoft Parallel Data Warehouse integrates beautifully with other Microsoft ecosystem products."
"The UI is very simple and functional for my clients, most of the clients that use the solution are not experts."
"We are able to monitor daily jobs, so if there is anything that needs to be done then we can do it."
"I am very satisfied with the customer service/technical support."
"It performs very well overall."
"The most valuable features of Snowflake are that you have to pay per usage, and you don't have to worry about the maintenance of the data warehouse because it is on the cloud."
"The overall ecosystem was easy to manage. Given that we weren't a very highly technical group, it was preferable to other things we looked at because it could do all of the cloud tunings. It can tune your data warehouse to an appropriate size for controlled billing, resume and sleep functions, and all such things. It was much more simple than doing native Azure or AWS development. It was stable, and their support was also perfect. It was also very easy to deploy. It was one of those rare times where they did exactly what they said they could do."
"The solution is very stable."
"The initial setup is very simple."
"It requires no maintenance on our part. They handle all that. The speed is phenomenal. The pricing isn't really anything more than what you would be paying for a SQL server license or another tool to execute the same thing. We have zero maintenance on our side to do anything and the speed at which it performs queries and loads the data is amazing. It handles unstructured data extremely well, too. So, if the data is in a JSON array or an XML, it handles that super well."
"Working with Parquet files is support out of the box and it makes large dataset processing much easier."
"The way it is built and designed is valuable. The way the shared model is built and the way it exploits the power of the cloud is very good. Certain features related to administration and management, akin to Oracle Flashback and all that, are very important for modern-day administration and management. It is also good in terms of managing and improving performance, indexing, and partitioning. It is sort of completely automated. Everything is essentially under the hood, and the engine takes care of it all. As a data warehouse on the cloud, Snowflake stands strong on its ground even though each of the cloud providers has its own data warehouse, such as Redshift for AWS or Synapse for Azure."
"It is very fast and the performance is great."
"The product does not have all of the features that the native products have."
"We'd like to see it be a bit more compatible with other solutions."
"We find the cost of the solution to be a little high."
"More tools to help designers should be included."
"The product must provide more frequent updates."
"Concurrent queries are limited to 32, making it more of a data storage mechanism instead of an active DWH solution."
"Sometimes, the product requires rolling back to its previous version during a software update. This particular area could be enhanced."
"I would like the tool to support different operating systems."
"Maybe there could be some more connectors to other systems, but this is what they are constantly developing anyway."
"It's not that flexible when compared to Oracle."
"There is a scope for improvement. They don't currently support integration with some of the Azure and AWS native services. It would be good if they can enhance their product to integrate with these services."
"Its transaction application needs improvement."
"From the documentation, the black box is not very descriptive. Snowflake does not reveal how exactly the data is processed or sourced."
"Sometimes it can be tricky to manage multiple environments if you're purely using Snowflake as your scripting and pipeline environment."
"The solution should offer an on-premises version also. We have some requirements where we would prefer to use it as a template."
"We would like to see more security including more masking and more encryption at the database level."
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Microsoft Parallel Data Warehouse is ranked 9th in Data Warehouse with 32 reviews while Snowflake is ranked 1st in Data Warehouse with 94 reviews. Microsoft Parallel Data Warehouse is rated 7.6, while Snowflake is rated 8.4. The top reviewer of Microsoft Parallel Data Warehouse writes "An easy to setup tool that allows its users to write stored procedure, making it a scalable product". 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 Parallel Data Warehouse is most compared with Microsoft Azure Synapse Analytics, Oracle Exadata and SAP BW4HANA, whereas Snowflake is most compared with BigQuery, Azure Data Factory, Teradata, Vertica and AWS Lake Formation. See our Microsoft Parallel Data Warehouse vs. Snowflake report.
See our list of best Data Warehouse vendors and best Cloud Data Warehouse vendors.
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