Compare Microsoft Parallel Data Warehouse vs. Pivotal Greenplum

Microsoft Parallel Data Warehouse is ranked 7th in Data Warehouse with 10 reviews while Pivotal Greenplum is ranked 8th in Data Warehouse with 4 reviews. Microsoft Parallel Data Warehouse is rated 7.0, while Pivotal Greenplum is rated 7.8. 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 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: January 2020.
389,772 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.

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The most valuable feature for us is horizontal scaling.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.

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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.

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I saw some limitation with respect to the column store, and removing this would be an improvement.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.

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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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We are using the open-source version of this solution.Pricing is good compared to other products. It's fine.

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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
8th
out of 30 in Data Warehouse
Views
12,022
Comparisons
8,513
Reviews
4
Average Words per Review
502
Avg. Rating
7.8
Top Comparisons
Compared 39% of the time.
Compared 12% 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.

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Learn more about Microsoft Parallel Data Warehouse
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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
REVIEWERS
Software R&D Company30%
Manufacturing Company10%
Insurance Company10%
Hospitality Company10%
REVIEWERS
Financial Services Firm44%
Marketing Services Firm19%
Comms Service Provider19%
Retailer6%
VISITORS READING REVIEWS
Software R&D Company27%
Financial Services Firm20%
Comms Service Provider11%
Insurance Company6%
Find out what your peers are saying about Microsoft Parallel Data Warehouse vs. Pivotal Greenplum and other solutions. Updated: January 2020.
389,772 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.