Compare Microsoft Parallel Data Warehouse vs. Pivotal Greenplum

Microsoft Parallel Data Warehouse is ranked 13th in Data Warehouse with 2 reviews while Pivotal Greenplum which is ranked 8th in Data Warehouse with 4 reviews. Microsoft Parallel Data Warehouse is rated 4.6, while Pivotal Greenplum is rated 8.0. The top reviewer of Microsoft Parallel Data Warehouse writes "Concurrency issues forced the customer to use the raw DB as a secondary solution". On the other hand, the top reviewer of Pivotal Greenplum writes "Handles complex queries and report production efficiently, integrates with Hadoop". Microsoft Parallel Data Warehouse is most compared with Oracle Exadata, Snowflake and Teradata, whereas Pivotal Greenplum is most compared with Apache Hadoop, Amazon Redshift and Teradata. See our Microsoft Parallel Data Warehouse vs. Pivotal Greenplum report.
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Most Helpful Review
Find out what your peers are saying about Microsoft Parallel Data Warehouse vs. Pivotal Greenplum and other solutions. Updated: July 2019.
361,263 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
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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Scalability is simple because it's an MPP database. If you need more processing power or you need more storage, you just add a few more nodes in the cluster. It works on common commodity hardware. You can use any type of server. You don't need to have proprietary hardware. It's fairly flexible.We chose Greenplum because of the architecture in terms of clustering databases and being able to have, or at least utilize the resources that are sitting on a database.It's one of the fastest databases in the market. It's easy to use. From a maintenance perspective it's a good product. The segmentation, or architecture of the product is different than other databases such as Oracle. So even in 10 years, the data distribution for such segments will not affect other segments. The query performance of the product, for complex queries, is very good. It has good integration with Hadoop.Very fast for query processing.

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Cons
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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Some integration with other platforms like design tools, and ETL development tools, that will enable some advanced functionality, like fully down processing, etc.The installation is difficult and should be made easier.Implementation takes a long time.One of the disadvantages, not a disadvantage with the product itself, but overall, is the expertise in the marketplace. It's not easy to find a Greenplum administrator in the market, compared to other products such as Oracle.they need to interact more with customers. They need to explain the features, especially when there are new releases of Greenplum. I know just from information I've found that it has other features, it can be used to for analytics, for integration with Big Data, Hadoop. They need to focus on this part with the customer.They need to enhance integration with other Big Data products... to integrate with Big Data platforms, and to open a bi-directional connection between Greenplum and Big Data.It will be very useful if we could communicate with other database types from Greenplum (using a database link).

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Pricing and Cost Advice
Information Not Available
Pricing is good compared to other products. It's fine.It is the best product with best fit for price/performance customer objectives.

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Ranking
13th
out of 30 in Data Warehouse
Views
6,784
Comparisons
2,310
Reviews
2
Average Words per Review
116
Avg. Rating
4.5
8th
out of 30 in Data Warehouse
Views
20,120
Comparisons
7,890
Reviews
4
Average Words per Review
524
Avg. Rating
8.0
Top Comparisons
Compared 44% of the time.
Compared 11% of the time.
Compared 11% of the time.
Also Known As
Microsoft PDW, SQL Server Data Warehouse, Microsoft SQL Server Parallel Data WarehouseGreenplum
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Microsoft
Pivotal
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.

Advanced analytics meets traditional business intelligence with Pivotal Greenplum, the world’s first fully-featured, multi-cloud, massively parallel processing (MPP) data platform based on the open source Greenplum Database. Pivotal Greenplum provides comprehensive and integrated analytics on multi-structured data. Powered by one of the world’s most advanced cost-based query optimizers, Pivotal Greenplum delivers unmatched analytical query performance on massive volumes of data.

Offer
Learn more about Microsoft Parallel Data Warehouse
Learn more about Pivotal Greenplum
Sample Customers
Auckland Transport, Erste Bank Group, Urban Software Institute, NJVC, Sheraton Hotels and Resorts, Tata Steel EuropeGeneral Electric, Conversant, China CITIC Bank, Aridhia, Purdue University
Top Industries
No Data Available
REVIEWERS
Financial Services Firm44%
Comms Service Provider19%
Marketing Services Firm19%
Software R&D Company6%
VISITORS READING REVIEWS
Financial Services Firm41%
Comms Service Provider9%
Manufacturing Company8%
Transportation Company5%
Company Size
REVIEWERS
Small Business38%
Midsize Enterprise13%
Large Enterprise50%
REVIEWERS
Small Business17%
Midsize Enterprise17%
Large Enterprise65%
VISITORS READING REVIEWS
Small Business33%
Midsize Enterprise27%
Large Enterprise39%
Find out what your peers are saying about Microsoft Parallel Data Warehouse vs. Pivotal Greenplum and other solutions. Updated: July 2019.
361,263 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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