Microsoft Parallel Data Warehouse vs Teradata comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Microsoft Parallel Data War...
Ranking in Data Warehouse
9th
Average Rating
7.6
Number of Reviews
33
Ranking in other categories
No ranking in other categories
Teradata
Ranking in Data Warehouse
3rd
Average Rating
8.2
Number of Reviews
56
Ranking in other categories
Relational Databases Tools (7th)
 

Mindshare comparison

As of July 2024, in the Data Warehouse category, the mindshare of Microsoft Parallel Data Warehouse is 0.3%, down from 1.0% compared to the previous year. The mindshare of Teradata is 15.2%, up from 14.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Warehouse
Unique Categories:
No other categories found
Relational Databases Tools
5.7%
 

Q&A Highlights

it_user104457 - PeerSpot reviewer
Apr 13, 2014
 

Featured Reviews

DJ Kim - PeerSpot reviewer
Apr 9, 2024
Enhances data management process with efficient integration capabilities
Our customers use Microsoft Parallel Data Warehouse to manage large volumes of data and perform complex queries efficiently. Its performance is generally superior compared to other solutions, aiding in the efficient handling of large-scale data analytics projects The key features impacting our…
SurjitChoudhury - PeerSpot reviewer
Feb 20, 2024
Offers seamless integration capabilities and performance optimization features, including extensive indexing and advanced tuning capabilities
We created and constructed the warehouse. We used multiple loading processes like MultiLoad, FastLoad, and Teradata Pump. But those are loading processes, and Teradata is a powerful tool because if we consider older technologies, its architecture with nodes, virtual processes, and nodes is a unique concept. Later, other technologies like Informatica also adopted the concept of nodes from Informatica PowerCenter version 7.x. Previously, it was a client-server architecture, but later, it changed to the nodes concept. Like, we can have the database available 24/7, 365 days. If one node fails, other nodes can take care of it. Informatica adopted all those concepts when it changed its architecture. Even Oracle databases have since adapted their architecture to them. However, this particular Teradata company initially started with its own different type of architecture, which major companies later adopted. It has grown now, but initially, whatever query we sent it would be mapped into a particular component. After that, it goes to the virtual processor and down to the disk, where the actual physical data is loaded. So, in between, there's a map, which acts like a data dictionary. It also holds information about each piece of data, where it's loaded, and on which particular virtual processor or node the data resides. Because Teradata comes with a four-node architecture, or however many nodes we choose, the cost is determined by that initially. So, what type of data does each and every node hold? It's a shared-no architecture. So, whatever task is given to a virtual processor it will be processed. If there's a failure, then it will be taken care of by another virtual processor. Moreover, this solution has impacted the query time and data performance. In Teradata, there's a lot of joining, partitioning, and indexing of records. There are primary and secondary indexes, hash indexing, and other indexing processes. To improve query performance, we first analyze the query and tune it. If a join needs a secondary index, which plays a major role in filtering records, we might reconstruct that particular table with the secondary index. This tuning involves partitioning and indexing. We use these tools and technologies to fine-tune performance. When it comes to integration, tools like Informatica seamlessly connect with Teradata. We ensure the Teradata database is configured correctly in Informatica, including the proper hostname and properties for the load process. We didn't find any major complexity or issues with integration. But, these technologies are quite old now. With newer big data technologies, we've worked with a four-layer architecture, pulling data from Hadoop Lake to Teradata. We configure Teradata with the appropriate hostname and credentials, and use BTEQ queries to load data. Previously, we converted the data warehouse to a CLD model as per Teradata's standardized procedures, moving from an ETL to an EMT process. This allowed us to perform gap analysis on missing entities based on the model and retrieve them from the source system again. We found Teradata integration straightforward and compatible with other tools.

Quotes from Members

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

Pros

"Microsoft Parallel Data Warehouse provides good firewall processing in terms of response time."
"It performs very well overall."
"I am very satisfied with the customer service/technical support."
"The most valuable feature is the business intelligence (BI) part of it."
"We can store the data in a data lake for a very low cost."
"​It has allowed fast daily loads and analysis of millions of rows of data, which eventually moved to near real-time.​"
"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 for me is querying."
"It handles large amounts of information with a linear performance increase, in relation to a HW investment."
"The solution scales well on the cloud."
"​We really enjoy the FastLoad, TPump, and MultiLoad features.​"
"The key advantages are Performance when processing Terabytes of data and scalability."
"The flexibility in design is very good."
"The most valuable feature of Teradata is security. It runs on Unix and Linux platforms which provide better security."
"​Building a data warehouse with Teradata has definitely helped a lot of our downstream applications to more easily access information."
"Their extensive experience in data warehousing, the platform's performance, and their strong reputation in the market are the most valuable."
 

Cons

"I would like the ability to do more real-time type updates instead of batch-oriented updates."
"I would like to see better visualization features."
"We find the cost of the solution to be a little high."
"The product must provide more frequent updates."
"Sometimes, the product requires rolling back to its previous version during a software update. This particular area could be enhanced."
"If the database is large with a lot of columns then it is difficult to clean the data."
"It could offer more development across the solution."
"SQL installation is pretty tricky. The scalability and customer support also should be improved."
"I'm not sure about the unstructured data management capabilities. It could be improved."
"The capability to implement it with comparable performance across various private cloud environments, ensuring adaptability to different infrastructure setups would be beneficial."
"Apart from Control-M, it would be nice if it could integrate with other tools."
"We tried to use case Teradata for a data warehouse system, but we had some problems in relation to the Teradata system, CDC tools, and source databases. We were unable to transfer data from HPE Integrity mainframe to Teradata."
"Azure Synapse SQL has evolved from a solely dedicated support tool to a data lake. It can store data from multiple systems, not just traditional database management systems. On the other hand, Teradata has limitations in loading flat files or unstructured data directly into its warehouse. In Azure Synapse SQL, we can implement machine learning using Python scripts. Additionally, Azure Synapse SQL offers advanced analytical capabilities compared to Teradata. Teradata is also expensive."
"Teradata can improve the way it handles big data and unstructured data."
"The user interface needs to be improved."
"I would like to see an improved Knowledge Base on the web."
 

Pricing and Cost Advice

"The solution's pricing is fairly decent for organizations with huge data sizes."
"They offer an annual subscription. The pricing depends on the size of the environments."
"I think the program is well-priced compared to the other offerings that are out in the market."
"All the features that we use do not require any additional subscription or yearly fees."
"Technical support is an additional fee and is expensive."
"The tool could be expensive if we need to manage a lot of data."
"The solution is cost-effective."
"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."
"In the past, it turned out that other solutions, in order to provide the full range of abilities that the Teradata platform provides plus the migration costs, would end up costing more than Teradata does."
"The initial cost may seem high, but the TCO is low."
"The solution requires a license."
"The price of Teradata is expensive. However, what they deliver they are outstanding. If you're looking for an inexpensive solution to run a database, this isn't your tool. It's the Ferrari of databases for data warehousing."
"I rate the product price a nine on a scale of one to ten, where one is cheap and ten is expensive."
"It's a very expensive product."
"Teradata is expensive but gives value for money, especially if you don't want to move your data to the cloud."
"It is still a very expensive solution. While I very much like the pure technological supremacy of the software itself, I believe Teradata as a company needs to become more affordable. They are already losing the market to more flexible or cheaper competitors."
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Comparison Review

it_user232068 - PeerSpot reviewer
Aug 5, 2015
Netezza vs. Teradata
Original published at https://www.linkedin.com/pulse/should-i-choose-net Two leading Massively Parallel Processing (MPP) architectures for Data Warehousing (DW) are IBM PureData System for Analytics (formerly Netezza) and Teradata. I thought talking about the similarities and differences…
 

Answers from the Community

it_user104457 - PeerSpot reviewer
Apr 13, 2014
Apr 13, 2014
I think hands down it's Exadata since for the front end apps it's just another Oracle database which means everything under the sun is compatible with it.
2 out of 3 answers
it_user89046 - PeerSpot reviewer
Apr 10, 2014
Given we partner with many or all of the above, or can get to them as we access all data, I have the following opinion - InfoBright is very new and probable to be sold long term. It is also an expensive subscription so presents highest risk to me. Exidata is Oracle - if you like Oracle and their style, it maybe ok, but then it is Oracle. Microsoft is Microsoft - tends to be cheap to acquire and expensive to implement and maintain. Teradata is pricey but of the group presents the least risk and the greatest number of front end partners. The product I represent is unique as it is designed for high complexity large numbers of users and data and runs inside Teradata taking better advantage of the architecture. Disclosure: I work for Information Builders
it_user3309 - PeerSpot reviewer
Apr 10, 2014
You are asking about front end tools but you do not mention which ones. What you have are "database backends" and each has different features. The utilization will depend on what kind of expertise you have available else you will end up trying to implement say, Teradata on Exadata which may not give you the best solution. What are your criteria for success? Based on these you will have to evaluate each solution -- I am sure each vendor will be happy to set up the environment and work with your set of sampl,e data to show you have they evaluate against your criteria.
 

Top Industries

By visitors reading reviews
Computer Software Company
25%
Financial Services Firm
16%
Insurance Company
7%
University
6%
Financial Services Firm
26%
Computer Software Company
10%
Manufacturing Company
8%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Microsoft Parallel Data Warehouse?
Microsoft Parallel Data Warehouse provides good firewall processing in terms of response time.
What is your experience regarding pricing and costs for Microsoft Parallel Data Warehouse?
They offer an annual subscription. The pricing depends on the size of the environments.
What needs improvement with Microsoft Parallel Data Warehouse?
Sometimes, the product requires rolling back to its previous version during a software update. This particular area could be enhanced.
Comparing Teradata and Oracle Database, which product do you think is better and why?
I have spoken to my colleagues about this comparison and in our collective opinion, the reason why some people may declare Teradata better than Oracle is the pricing. Both solutions are quite simi...
Which companies use Teradata and who is it most suitable for?
Before my organization implemented this solution, we researched which big brands were using Teradata, so we knew if it would be compatible with our field. According to the product's site, the comp...
Is Teradata a difficult solution to work with?
Teradata is not a difficult product to work with, especially since they offer you technical support at all levels if you just ask. There are some features that may cause difficulties - for example,...
 

Also Known As

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

Overview

 

Sample Customers

Auckland Transport, Erste Bank Group, Urban Software Institute, NJVC, Sheraton Hotels and Resorts, Tata Steel Europe
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Find out what your peers are saying about Microsoft Parallel Data Warehouse vs. Teradata and other solutions. Updated: June 2024.
792,098 professionals have used our research since 2012.