Microsoft Parallel Data Warehouse vs. Vertica

Microsoft Parallel Data Warehouse is ranked 11th in Data Warehouse with 3 reviews vs Vertica which is ranked 3rd in Data Warehouse with 16 reviews. The top reviewer of Microsoft Parallel Data Warehouse writes "Gives us the ability to distribute large data sets across nodes". The top reviewer of Vertica writes "The architecture means it can process/ingest data in parallel to reporting and analyzing because of in-memory Write-Optimized Storage alongside the analytics optimized Read-Optimized Storage". Microsoft Parallel Data Warehouse is most compared with Oracle Exadata, Teradata and Netezza. Vertica is most compared with Oracle Exadata, Teradata and Pivotal Greenplum. See our Microsoft Parallel Data Warehouse vs. Vertica report.
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Quotes From Members Comparing Microsoft Parallel Data Warehouse vs. Vertica

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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Vertica's most outstanding features are the compression rates achieved and the speed of access of high volume data.Allows us to take volumes and process them at a very high speed.Bulk loads, batch loads, and micro-batch loads have made it possible for our organization to process near real-time ingestions and faster analytics.Any novice user can tune vertical queries with minimal training (or no training at all).Vertica gives knowledgeable users and DBAs excellent tools for tuning.Its projections and encoding are excellent tools for tuning large volumes.Its analytics has enabled Pythian's clients to get the business insights as quick as they wanted. Its lower maintenance has also improved the ROI.The feature of the product that is most important is the speed. I needed a columnar database, and its speed is what it's built to do, and so that's what really does differentiate Vertica from its competitors.

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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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Support is an area where it could get better.Promotion/marketing must be improved, even though it is a very useful product at very good price, it is not as "popular" as it should be.It should provide a GUI interface for data management and tuning.Monitoring tools need to be lightweight. They should not take up heavy resources of the main server.If you do not utilize the tuning tools like projections, encoding, partitions, and statistics, then performance and scalability will suffer.It would be great if this were a managed service in AWS.One feature, which has really benefited us, is the scalability offered by Vertica as it has enabled Pythian's clients to manage data with agility.I believe the installation process could be streamlined.

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Pricing and Cost Advice
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Read the fine print carefully.I think it's starting to get a little expensive. Open source products are starting to get more robust, so I think that's something that they need to start looking at in terms of licensing.The first TB is free and you can use all the Vertica features. After 1TB you have to pay for licensing. The product is worth it, but be aware of this condition, and plan. The compression ratio is explained in the documentation.Start with license per 1TB. Starting from hundreds of TB there is unlimited licensing to be considered. Move historical data to HDFS/S3 which are significantly cheaper or even free.It's free up to three nodes and 1TB, and then get in contact with their sales guys.

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Ranking
Views
5,743
Comparisons
2,879
Reviews
3
Followers
439
Avg. Rating
5.7
Views
24,461
Comparisons
7,730
Reviews
16
Followers
749
Avg. Rating
8.6
Views
0
Comparisons
0
Reviews
1
Followers
1
Avg. Rating
5.0
Top Comparisons
See more Microsoft Parallel Data Warehouse competitors »
Compared 19% of the time.
Compared 16% of the time.
Compared 12% of the time.
See more Vertica competitors »
Also Known As
Microsoft PDW, SQL Server Data Warehouse, Microsoft SQL Server Parallel Data WarehouseMicro Focus Vertica, HPE Vertica, HPE Vertica on Demand
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Microsoft
Micro Focus
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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.

Micro Focus Vertica is the most advanced SQL database analytics portfolio built from the very first line of code to address the most demanding Big Data analytics initiatives. Micro Focus Vertica delivers speed without compromise, scale without limits, and the broadest range of consumption models. Choose Vertica on premise, on demand, in the cloud, or on Hadoop. With support for all leading BI and visualization tools, open source technologies like Hadoop and R, and built-in analytical functions, Vertica helps you derive more value from your Enterprise Data Warehouse and data lakes and get to market faster with your analytics initiatives.

To learn more about Micro Focus Vertica Advanced Analytics, visit our website.

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Sample Customers
Auckland Transport, Erste Bank Group, Urban Software Institute, NJVC, Sheraton Hotels and Resorts, Tata Steel EuropeCerner, Game Show Network Game, Guess by Marciano, Supercell, Etsy, Nascar, Empirix, adMarketplace, and Cardlytics.
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Top Industries
VISITORS READING REVIEWS
Financial Services Firm
21%
Hospitality Company
10%
Comms Service Provider
9%
Insurance Company
8%
REVIEWERS
Media Company
21%
Software R&D Company
21%
Marketing Services Firm
17%
Comms Service Provider
14%
VISITORS READING REVIEWS
Financial Services Firm
21%
Comms Service Provider
19%
Marketing Services Firm
9%
Media Company
9%
No Data Available
Company Size
REVIEWERS
Small Business
38%
Midsize Enterprise
13%
Large Enterprise
50%
VISITORS READING REVIEWS
Small Business
11%
Midsize Enterprise
19%
Large Enterprise
70%
REVIEWERS
Small Business
29%
Midsize Enterprise
24%
Large Enterprise
47%
VISITORS READING REVIEWS
Small Business
23%
Midsize Enterprise
25%
Large Enterprise
52%
No Data Available
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