We performed a comparison between Microsoft Parallel Data Warehouse and Snowflake Analytics based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable feature of this solution is performance."
"Microsoft Parallel Data Warehouse integrates beautifully with other Microsoft ecosystem products."
"It is a stable solution...It is a scalable solution."
"The solution has been reliable."
"I am very satisfied with the customer service/technical support."
"It performs very well overall."
"We are able to monitor daily jobs, so if there is anything that needs to be done then we can do it."
"The most valuable features are the performance and usability."
"Time Travel and Snowpipe are good features."
"Its performance speed is very good."
"Scaling is very high – there's no problem for scaling purposes. The learning curve is very small. And there are a lot of advanced features like handling duplicates, security, data governance, data sharing, and data cloning."
"Very good flexibility and it offers computation completely decoupled from the storage."
"I am impressed with the product's data-sharing feature."
"Considering everything I have accessed, the product's dashboard is good since it provides multiple good options, including customization options."
"Snowflake Analytics' most valuable feature is its inbuilt infrastructure for executing queries, which I don't have to manage based on my data volume as it's taken care of by Snowflake."
"Scalability-wise, I rate the solution a ten out of ten."
"The product does not have all of the features that the native products have."
"Concurrent queries are limited to 32, making it more of a data storage mechanism instead of an active DWH solution."
"It could offer more development across the solution."
"The product must provide more frequent updates."
"The only issue with the product is that the process is very slow when we have a huge amount of data."
"Sometimes, the product requires rolling back to its previous version during a software update. This particular area could be enhanced."
"If the database is large with a lot of columns then it is difficult to clean the data."
"In the future I would love to see a slightly better automation engine, just for the data integration layer, to make it slightly easier for end-users or junior developers to get involved in incremental updating."
"I cannot comment on the product's stability because we are still struggling with its performance."
"Snowflake's Snowpark is an area of concern where improvements are required."
"The product's cost is an area of concern where improvements are required."
"Integration into different Python and Jupyter notebooks needs to be improved."
"End-to-end execution of jobs isn't possible with Snowflake, which means we have to do some customization."
"The solution’s interface is good but it could be improved."
"The technical support is not very good."
"Snowflake should include a WHERE clause for building data pipelines."
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Microsoft Parallel Data Warehouse is ranked 8th in Data Warehouse with 32 reviews while Snowflake Analytics is ranked 7th in Cloud Data Warehouse with 29 reviews. Microsoft Parallel Data Warehouse is rated 7.6, while Snowflake Analytics 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 Analytics writes "A scalable tool useful for data lake and data mining processes". Microsoft Parallel Data Warehouse is most compared with Microsoft Azure Synapse Analytics, Oracle Exadata, SAP BW4HANA, VMware Tanzu Greenplum and Snowflake, whereas Snowflake Analytics is most compared with Azure Data Factory, Adobe Analytics, Mixpanel, Amplitude and Glassbox. See our Microsoft Parallel Data Warehouse vs. Snowflake Analytics report.
See our list of best Cloud Data Warehouse vendors.
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.
