Compare Microsoft Parallel Data Warehouse vs. Netezza

Microsoft Parallel Data Warehouse is ranked 13th in Data Warehouse with 4 reviews while Netezza is ranked 6th in Data Warehouse with 8 reviews. Microsoft Parallel Data Warehouse is rated 6.6, while Netezza is rated 7.6. 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 Netezza writes "The underlying hardware is made for performance on large amounts of data, and for analytics". Microsoft Parallel Data Warehouse is most compared with Oracle Exadata, Snowflake and Teradata, whereas Netezza is most compared with Oracle Exadata, SQL Server and IBM Db2. See our Microsoft Parallel Data Warehouse vs. Netezza report.
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Most Helpful Review
Find out what your peers are saying about Microsoft Parallel Data Warehouse vs. Netezza and other solutions. Updated: November 2019.
382,547 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
The most valuable features are the performance and usability.I am very satisfied with the customer service/technical support.It handles high volumes of data very well.​It has allowed fast daily loads and analysis of millions of rows of data, which eventually moved to near real-time.​

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The performance is most important to me, and it helps our ability to make business decisions quickly.We are able to execute very complex queries. Over 90 percent of our query executions are one second or less. We do millions of queries everyday.The underlying hardware that IBM provides with this appliance is made for a specific purpose, to serve performance on a large amount of data, and to do analytics as well. It is faster, when you compare it to any other product.The most valuable feature would be the fact that it has been running for awhile in an appliance format.The benefit is really because of the additional speed that we have and, truth be told, the more updated ETL processes and the revamped scheduler in general.The data governance prospect... from what I've seen, that is a really powerful tool as well, to help with data lineage and keeping track of that.Distribution concurrency control.

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Cons
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.​Concurrent queries are limited to 32, making it more of a data storage mechanism instead of an active DWH solution.

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The scalability is not as expected. The capacity in the black box is not enough.Our main problem with it is concurrency. When there are too many users running Netezza at the same time, this is when we have the most complaints.We are not able to scale. The only way to scale is to get another appliance, but we have a customers who would need us to hydrate the data between the two appliances, and Netezza does not do that.The only issue is that it's not expandable.In terms of features that I would like to see, one is the ability to actually scale out an architecture. Right now, if you buy one, it's fixed. There is no scale-up availability at all.Concurrency limit needs to be increased somewhat.LIke Teradata, we can’t add a node/SPU to the existing appliance.

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

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The pricing is very expensive. It has a lot CPUs with a lot of components in it. It also has built-in redundancy for resiliency reasons.Netezza is a costly solution. It does serve a specific purpose but it's costlier than what's available in the market, if you go to the cloud.

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Ranking
13th
out of 30 in Data Warehouse
Views
2,866
Comparisons
2,107
Reviews
3
Average Words per Review
310
Avg. Rating
6.0
6th
out of 30 in Data Warehouse
Views
9,881
Comparisons
6,775
Reviews
8
Average Words per Review
548
Avg. Rating
7.6
Top Comparisons
Compared 29% of the time.
Compared 13% of the time.
Compared 7% of the time.
Also Known As
Microsoft PDW, SQL Server Data Warehouse, Microsoft SQL Server Parallel Data Warehouse
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Microsoft
IBM
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.

IBM Netezza appliances are now part of IBM PureSystems - expert integrated systems with built in expertise, integration by design and a simplified user experience. Part of the PureData family, the Netezza appliance is now known as the PureData System for Analytics. It has the same key design tenets of simplicity, speed, scalability and analytics power that was fundamental to Netezza appliances.
Offer
Learn more about Microsoft Parallel Data Warehouse
Learn more about Netezza
Sample Customers
Auckland Transport, Erste Bank Group, Urban Software Institute, NJVC, Sheraton Hotels and Resorts, Tata Steel EuropeSeattle Childrens Hospital, Carphone Warehouse, Vanderbilt University School of Medicine, Battelle, Start Today Co. Ltd., Kelley Blue Book, Trident Marketing, Elisa Corporation, Catalina Marketing, iBasis, Barnes & Noble, Qualcomm, MediaMath, Acxiom, iBasis, Foxwoods
Top Industries
No Data Available
REVIEWERS
Financial Services Firm40%
Comms Service Provider13%
Retailer13%
Pharma/Biotech Company7%
VISITORS READING REVIEWS
Software R&D Company38%
Retailer12%
Comms Service Provider10%
Financial Services Firm8%
Find out what your peers are saying about Microsoft Parallel Data Warehouse vs. Netezza and other solutions. Updated: November 2019.
382,547 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.
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