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."We are able to monitor daily jobs, so if there is anything that needs to be done then we can do it."
"We have complete control over our data."
"It performs very well overall."
"The most valuable feature of this solution is performance."
"I like Data Warehouse's data integrity features. Data integrity is what databases are made for as opposed to spreadsheets."
"It handles high volumes of data very well."
"The solution's integration is good."
"Tools like the BI and SAS are excellent."
"It is a very easy-to-use solution. It is user-friendly, and its setup time is very less."
"From a data warehouse perspective, it's an excellent all-round solution. It's very complete."
"The best thing about Snowflake is its flexibility in changing warehouse sizes or computational power."
"Snowflake has three great features: Snowpiping is proving to be very valuable, Time Travel is excellent, and Snowpipes are another great functionality the solution has made available."
"All the people who are working with Snowflake are extremely happy with it because it is designed from a data-warehousing point of view, not the other way around. You have a database and then you tweak it and then it becomes a data warehouse."
"For us, the virtual warehousing is likely the most valuable aspect."
"The pricing is reasonable and matches the rest of the market."
"Snowflake is a database, and it is very good and useful. The most interesting part is that memory management is very good in Snowflake. For a business intelligence project, SQL Server is taking a lot of time for reporting services. There are a lot of calculations, and the reporting time is shown as two minutes, whereas Snowflake is taking just two seconds for the same reporting services."
"I would like the tool to support different operating systems."
"It could be made more user-friendly for business users which would increase the user base."
"Sometimes, the product requires rolling back to its previous version during a software update. This particular area could be enhanced."
"The feature updates on the on-premise solution come very slowly, and it would be great if they came faster."
"The solution is expensive and has room for improvement."
"The product must provide more frequent updates."
"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 would like to see better visualization features."
"There could be better ELT tools that are appropriate for Snowflake. We decided on Matillion and it seemed to be the only one. There need to be better choices, it would be great if Snowflake provided an ELT solution that people could use. Additionally, if there was a pure cloud-based ELT tool it would be useful."
"It's not that flexible when compared to Oracle."
"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."
"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."
"There are some stored procedures that we've had trouble with. The solution also needs to fine-tune the connectors to be able to connect into the system source."
"I think that Snowflake could improve its user interface. The current one is not interactive."
"Snowflake needs to improve its programming part. Though the tool has Snowpath, it doesn’t support all features like its competitor, Databricks. Snowflake doesn’t support external data ingestion capabilities. You need to have third-party tools for that. Also, the tool needs to incorporate data integration features in its future releases."
"Snowflake can improve its machine learning and AI capabilities."
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Microsoft Parallel Data Warehouse is ranked 8th in Data Warehouse with 32 reviews while Snowflake is ranked 1st in Data Warehouse with 92 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, SAP BW4HANA and VMware Tanzu Greenplum, 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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