Compare Microsoft Parallel Data Warehouse vs. Snowflake

Microsoft Parallel Data Warehouse is ranked 7th in Data Warehouse with 10 reviews while Snowflake is ranked 4th in Data Warehouse with 10 reviews. Microsoft Parallel Data Warehouse is rated 7.0, while Snowflake is rated 8.2. The top reviewer of Microsoft Parallel Data Warehouse writes "It's well-priced, extremely stable and the technical support is very good". On the other hand, the top reviewer of Snowflake writes "Fast, convenient and requires almost no administration". Microsoft Parallel Data Warehouse is most compared with Oracle Exadata, Snowflake and Teradata, whereas Snowflake is most compared with Apache Hadoop, Microsoft Azure SQL Data Warehouse and Amazon Redshift. See our Microsoft Parallel Data Warehouse vs. Snowflake report.
Cancel
You must select at least 2 products to compare!
Most Helpful Review
Find out what your peers are saying about Microsoft Parallel Data Warehouse vs. Snowflake and other solutions. Updated: January 2020.
391,329 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
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 feature is the business intelligence (BI) part of it.The data transmissions between the data models is the most valuable feature.The most valuable feature of this solution is performance.One of the most important features is the ease of using MS SQL.The most valuable feature for me is querying.The most valuable features are the performance and usability.I am very satisfied with the customer service/technical support.

Read more »

I like the idea that you can assign roles and responsibilities, limiting access to data.It has great flexibility whenever we are loading data and performs ELT (extract, load, transform) techniques instead of ETL.The snapshot feature is good, the rollback feature is good and the interface is user-friendly.The thing I find most valuable is that scalability, space storage, and computing power is separate. When you scale up, it is live from one second to the next — constantly available as you scale — so there is no downtime or interruption of services.The initial setup is straightforward. You just need to follow the documentation.They separate compute and storage. You can scale storage independently of the computer, or you can scale computing independently of storage. If you need to buy more computer parts you can add new virtual warehouses in Snowflake. Similarly, if you need more storage, you take more storage. It's most scalable in the database essentially; typically you don't have this scalability independence on-premises.The most valuable features are the clustering, LS50, being able to change the size, the pay per use feature, the flexibility with many different sources and analytic applications.As long as you don't need to worry about the storage or cost, this solution would be one of the best ones on the market for scalability purposes.

Read more »

Cons
If the database is large with a lot of columns then it is difficult to clean the data.This solution would be improved with an option for in-memory data analysis.The reporting for certain types of data needs to be improved.I think that the error messages need to be made more specific.I would like to see better visualization features.More tools to help designers should be included.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.It needs more compatibility with common BI tools.

Read more »

If you go with one cloud provider, you can't switch.They do have a native connector to connect with integration tools for loading data, but it would be much better to have the functionality built-in.Availability is a problem.Maybe there could be some more connectors to other systems, but this is what they are constantly developing anyway.The solution could improve the user interface and add functionality to the system.The solution should offer an on-premises version also. We have some requirements where we would prefer to use it as a template.Support needs improvement, as it can take several days before you get some initial support.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.

Read more »

Pricing and Cost Advice
I think the program is well-priced compared to the other offerings that are out in the market.

Read more »

You pay based on the data that you are storing in the data warehouse and there are no maintenance costs.The whole licensing system is based on credit points. You can also make a license agreement with the company so that you buy credit points and then you use them. What you do not use in one year can be carried over to the next year.Pricing can be confusing for customers.

Read more »

report
Use our free recommendation engine to learn which Data Warehouse solutions are best for your needs.
391,329 professionals have used our research since 2012.
Ranking
7th
out of 30 in Data Warehouse
Views
2,865
Comparisons
2,093
Reviews
10
Average Words per Review
359
Avg. Rating
7.0
4th
out of 30 in Data Warehouse
Views
17,496
Comparisons
12,527
Reviews
8
Average Words per Review
669
Avg. Rating
8.3
Top Comparisons
Compared 24% of the time.
Compared 13% of the time.
Also Known As
Microsoft PDW, SQL Server Data Warehouse, Microsoft SQL Server Parallel Data WarehouseSnowflake Computing
Learn
Microsoft
Snowflake Computing
Overview

The traditional structured relational data warehouse was never designed to handle the volume of exponential data growth, the variety of semi-structured and unstructured data types, or the velocity of real time data processing. Microsoft's SQL Server data warehouse solution integrates your traditional data warehouse with non-relational data and it can handle data of all sizes and types, with real-time performance.

Snowflake provides a data warehouse built for the cloud, delivering a solution capable of solving problems for which legacy, on-premises and cloud data platforms were not designed.

Offer
Learn more about Microsoft Parallel Data Warehouse
Learn more about Snowflake
Sample Customers
Auckland Transport, Erste Bank Group, Urban Software Institute, NJVC, Sheraton Hotels and Resorts, Tata Steel EuropeAccordant Media, Adobe, Kixeye Inc., Revana, SOASTA, White Ops
Top Industries
REVIEWERS
Software R&D Company30%
Insurance Company10%
Hospitality Company10%
Healthcare Company10%
VISITORS READING REVIEWS
Software R&D Company37%
Financial Services Firm8%
Retailer7%
Comms Service Provider7%
Company Size
REVIEWERS
Small Business35%
Midsize Enterprise12%
Large Enterprise53%
REVIEWERS
Small Business20%
Midsize Enterprise20%
Large Enterprise60%
VISITORS READING REVIEWS
Small Business4%
Midsize Enterprise17%
Large Enterprise79%
Find out what your peers are saying about Microsoft Parallel Data Warehouse vs. Snowflake and other solutions. Updated: January 2020.
391,329 professionals have used our research since 2012.
We monitor all 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.