Compare Microsoft Azure SQL Data Warehouse vs. Microsoft Parallel Data Warehouse

Microsoft Azure SQL Data Warehouse is ranked 4th in Cloud Data Warehouse with 1 review while Microsoft Parallel Data Warehouse is ranked 14th in Data Warehouse with 2 reviews. Microsoft Azure SQL Data Warehouse is rated 9.0, while Microsoft Parallel Data Warehouse is rated 4.6. The top reviewer of Microsoft Azure SQL Data Warehouse writes "Easy to set up and use, good technical support, and works with a variety of SQL databases". On the other hand, the top reviewer of Microsoft Parallel Data Warehouse writes "Concurrency issues forced the customer to use the raw DB as a secondary solution". Microsoft Azure SQL Data Warehouse is most compared with Snowflake, Amazon Redshift and Teradata Cloud Data Warehouse, whereas Microsoft Parallel Data Warehouse is most compared with Oracle Exadata, Snowflake and Teradata.
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Most Helpful Review
Use Microsoft Azure SQL Data Warehouse? Share your opinion.
Find out what your peers are saying about Micro Focus, Snowflake Computing, Amazon and others in Cloud Data Warehouse. Updated: August 2019.
365,820 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
Scaling this solution is easy and the uptime is okay.

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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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Cons
I would like to see better integration with Active Directory, because we have had problems, and we still do.

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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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Pricing and Cost Advice
The price of this solution could be improved.

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365,820 professionals have used our research since 2012.
Ranking
4th
Views
6,696
Comparisons
6,060
Reviews
1
Average Words per Review
735
Avg. Rating
9.0
14th
out of 30 in Data Warehouse
Views
2,995
Comparisons
2,240
Reviews
2
Average Words per Review
116
Avg. Rating
4.5
Top Comparisons
Also Known As
Microsoft Azure SQL DW, Azure SQL Data WarehouseMicrosoft PDW, SQL Server Data Warehouse, Microsoft SQL Server Parallel Data Warehouse
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Microsoft
Microsoft
Overview

Azure SQL Data Warehouse is a Fast, flexible, and secure analytics platform for the enterprise. Azure SQL Data Warehouse lets you independently scale compute and storage, while pausing and resuming your data warehouse within minutes through a massively parallel processing architecture designed for the cloud. Seamlessly create your hub for analytics along with native connectivity with data integration and visualization services, all while using your existing SQL and BI skills.

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.

Offer
Learn more about Microsoft Azure SQL Data Warehouse
Learn more about Microsoft Parallel Data Warehouse
Sample Customers
Toshiba, Carnival, LG Electronics, Jet.com, Adobe, Auckland Transport, Erste Bank Group, Urban Software Institute, NJVC, Sheraton Hotels and Resorts, Tata Steel Europe
Top Industries
VISITORS READING REVIEWS
Manufacturing Company17%
Software R&D Company16%
Financial Services Firm14%
Outsourcing Company9%
No Data Available
Find out what your peers are saying about Micro Focus, Snowflake Computing, Amazon and others in Cloud Data Warehouse. Updated: August 2019.
365,820 professionals have used our research since 2012.
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.
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