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Apache Hadoop vs Microsoft Parallel Data Warehouse comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Apache Hadoop
Ranking in Data Warehouse
6th
Average Rating
7.8
Number of Reviews
39
Ranking in other categories
No ranking in other categories
Microsoft Parallel Data War...
Ranking in Data Warehouse
10th
Average Rating
7.8
Reviews Sentiment
7.4
Number of Reviews
34
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of November 2024, in the Data Warehouse category, the mindshare of Apache Hadoop is 5.1%, down from 6.2% compared to the previous year. The mindshare of Microsoft Parallel Data Warehouse is 1.0%, down from 1.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Warehouse
 

Featured Reviews

Sushil Arya - PeerSpot reviewer
Provides ease of integration with the IT workflow of a business
When working with Kafka, I saw that the data came in an incremental order. The incremental data processing part is still not very effective in Apache Hadoop. If the data is already there, it can be processed very effectively, especially if the data is coming in every second. If you want to know the location of some data every second, then such data is not processed effectively in Apache Hadoop. I can say that one of the features where improvements are required revolves around the licensing cost of the tool. If the tool can build some licensing structures in a pay-per-use manner, organizations can get the look and feel of Apache Hadoop. Apache Hadoop can offer a licensing structure of the product that can be seen as similar to how AWS operates. Apache Hadoop can look into the capability of processing incremental data. The tool's setup process can be a scope of improvement. Also, it is not very simple because while doing the setup, we need to do all the server settings, including port listing and firewall configurations. If we look at other products on the market, then they can be made simpler. There are certain shortcomings when it comes to the product's technical support part, making it an area where improvements are required. The time frame for the resolution is an area that needs to be improved. The overall communication part of the technical support team also needs improvement.
StevenLai - PeerSpot reviewer
Strong scalable solution with streamlined metadata warehousing
We use it to build our data warehouse and databases, and everything in the back end It helps streamline our metadata warehousing process. As it is our only type of data warehouse and database, it serves as our source, destination, and staging area. This product has many features which are useful…

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Two valuable features are its scalability and parallel processing. There are jobs that cannot be done unless you have massively parallel processing."
"The platform's quick data processing capabilities have been instrumental in supporting our AI-driven projects."
"Hadoop is extensible — it's elastic."
"Initially, with RDBMS alone, we had a lot of work and few servers running on-premise and on cloud for the PoC and incubation. With the use of Hadoop and ecosystem components and tools, and managing it in Amazon EC2, we have created a Big Data "lab" which helps us to centralize all our work and solutions into a single repository. This has cut down the time in terms of maintenance, development and, especially, data processing challenges."
"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."
"The solution is easy to expand. We haven't seen any issues with it in that sense. We've added 10 servers, and we've added two nodes. We've been expanding since we started using it since we started out so small. Companies that need to scale shouldn't have a problem doing so."
"The performance is pretty good."
"The most valuable features are the performance and usability."
"I am very satisfied with the customer service/technical support."
"Microsoft Parallel Data Warehouse provides good firewall processing in terms of response time."
"Data collection and reporting are valuable features of the solution."
"We are able to monitor daily jobs, so if there is anything that needs to be done then we can do it."
"Microsoft Parallel Data Warehouse integrates beautifully with other Microsoft ecosystem products."
"The most valuable feature for me is querying."
"One of the most important features is the ease of using MS SQL."
 

Cons

"The main thing is the lack of community support. If you want to implement a new API or create a new file system, you won't find easy support."
"The solution is very expensive."
"The key shortcoming is its inability to handle queries when there is insufficient memory. This limitation can be bypassed by processing the data in chunks."
"Improvements in security measures would be beneficial, given the large volumes of data handled."
"It needs better user interface (UI) functionalities."
"Real-time data processing is weak. This solution is very difficult to run and implement."
"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"There are certain shortcomings when it comes to the product's technical support part, making it an area where improvements are required."
"I would like the ability to do more real-time type updates instead of batch-oriented updates."
"The feature updates on the on-premise solution come very slowly, and it would be great if they came faster."
"It needs more compatibility with common BI tools."
"Sometimes, the product requires rolling back to its previous version during a software update. This particular area could be enhanced."
"The solution is expensive and has room for improvement."
"If the database is large with a lot of columns then it is difficult to clean the data."
"More tools to help designers should be included."
"The product does not have all of the features that the native products have."
 

Pricing and Cost Advice

"For any big enterprise the costs can be handled, and it is suitable for big enterprises because the scale of data is large. For medium and small enterprises, the tool is on the high-price side."
"The price of Apache Hadoop could be less expensive."
"The price could be better. Hortonworks no longer exists, and Cloudera killed the free version of Hadoop."
"The product is open-source, but some associated licensing fees depend on the subscription level."
"Do take into consider that data storage and compute capacity scale differently and hence purchasing a "boxed" / 'all-in-one" solution (software and hardware) might not be the best idea."
"We just use the free version."
"If my company can use the cloud version of Apache Hadoop, particularly the cloud storage feature, it would be easier and would cost less because an on-premises deployment has a higher cost during storage, for example, though I don't know exactly how much Apache Hadoop costs."
"This is a low cost and powerful solution."
"All the features that we use do not require any additional subscription or yearly fees."
"The solution's pricing is fairly decent for organizations with huge data sizes."
"I think the program is well-priced compared to the other offerings that are out in the market."
"Microsoft has an agreement with the government in our country, so our customers get their licensing costs from the Ministry. Whenever we work with any government, company, or government institute, which is mainly what we are doing, that license comes directly from the Ministry of Technology and Information."
"Technical support is an additional fee and is expensive."
"They offer an annual subscription. The pricing depends on the size of the environments."
"The tool could be expensive if we need to manage a lot of data."
"The solution is cost-effective."
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Top Industries

By visitors reading reviews
Financial Services Firm
32%
Computer Software Company
11%
University
7%
Energy/Utilities Company
6%
Computer Software Company
28%
Financial Services Firm
19%
Insurance Company
7%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Apache Hadoop?
It's primarily open source. You can handle huge data volumes and create your own views, workflows, and tables. I can also use it for real-time data streaming.
What is your experience regarding pricing and costs for Apache Hadoop?
The product is open-source, but some associated licensing fees depend on the subscription level. While it might be free for students, organizations typically need to pay for their subscriptions. Th...
What needs improvement with Apache Hadoop?
Hadoop lacks OLAP capabilities. I recommend adding a Delta Lake feature to make the data compatible with ACID properties. Also, video and audio streaming import issues could be improved to ensure p...
What do you like most about Microsoft Parallel Data Warehouse?
Microsoft Parallel Data Warehouse provides good firewall processing in terms of response time.
What needs improvement with Microsoft Parallel Data Warehouse?
There are many areas for improvement. A major issue is with table statistics. Sometimes the statistics are not refreshed correctly, which causes issues for us. When we update a table, it should tri...
 

Also Known As

No data available
Microsoft PDW, SQL Server Data Warehouse, Microsoft SQL Server Parallel Data Warehouse, MS Parallel Data Warehouse
 

Learn More

 

Overview

 

Sample Customers

Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab
Auckland Transport, Erste Bank Group, Urban Software Institute, NJVC, Sheraton Hotels and Resorts, Tata Steel Europe
Find out what your peers are saying about Apache Hadoop vs. Microsoft Parallel Data Warehouse and other solutions. Updated: November 2024.
816,406 professionals have used our research since 2012.