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Azure Data Factory vs IBM Netezza Performance Server comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

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

ROI

Sentiment score
6.8
Azure Data Factory offers cost-effective, efficient data consolidation for actionable insights, saving time and resources compared to manual processes.
Sentiment score
7.1
IBM Netezza Performance Server improves data query speed and efficiency, enhancing business performance and cost savings through compression.
Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
 

Customer Service

Sentiment score
6.4
Azure Data Factory support is generally satisfactory, with responsive assistance, though some users report delays or costly consulting.
Sentiment score
6.4
IBM Netezza Performance Server praised for knowledgeable support; mixed feedback on resolution speed post-acquisition, yet communication remains consistent.
The technical support is responsive and helpful
The technical support from Microsoft is rated an eight out of ten.
The technical support for Azure Data Factory is generally acceptable.
Technical support is very costly for me, accounting for twenty-five to thirty percent of the product cost.
 

Scalability Issues

Sentiment score
7.5
Azure Data Factory is highly scalable and flexible but has room for improvement with third-party integrations and large datasets.
Sentiment score
6.1
IBM Netezza struggles with scalability, requiring extra hardware for expansion, prompting users to consider cloud alternatives for growth.
Azure Data Factory is highly scalable.
It is provided as a pre-configured box, and scaling is not an option.
 

Stability Issues

Sentiment score
7.8
Azure Data Factory is stable and reliable, with occasional issues in responsiveness and large dataset handling.
Sentiment score
7.8
IBM Netezza Performance Server is stable, offering high uptime and reliable performance, with occasional issues due to maintenance or compatibility.
The solution has a high level of stability, roughly a nine out of ten.
 

Room For Improvement

Azure Data Factory needs better integration, scheduling, support, AI features, and user interface improvements for efficient data management.
IBM Netezza struggles with scalability, user interface, query performance, big data support, and high costs, needing better tools and integration.
There is a problem with the integration with third-party solutions, particularly with SAP.
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
When using Git services, there are challenges with linked services and triggers getting overridden when moving between different environments (Dev, UAT, Prod).
The cloud version is only available in AWS, and in the Middle East, it is not well-developed in the Azure environment.
 

Setup Cost

Azure Data Factory offers competitive, flexible pricing based on usage, with costs integrating Azure services and varying significantly.
IBM Netezza offers high performance and low maintenance but is considered costly, especially for mid-sized organizations, with significant licensing fees.
The pricing is cost-effective.
It is considered cost-effective.
 

Valuable Features

Azure Data Factory excels in data integration with user-friendly features, scalability, and over 100 connectors for seamless data movement.
IBM Netezza Performance Server delivers fast analytics, ease of use, robust support, and efficient data warehousing with minimal maintenance.
The orchestration features in Azure Data Factory are definitely useful, as it is not only for Azure Data Factory; we can also include DataBricks and other services for integrating the data solution, making it a very beneficial feature.
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
It connects to different sources out-of-the-box, making integration much easier.
It operates as a high-speed data warehouse, which is essential for handling big data.
 

Categories and Ranking

Azure Data Factory
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
92
Ranking in other categories
Data Integration (1st), Cloud Data Warehouse (2nd)
IBM Netezza Performance Server
Average Rating
7.8
Reviews Sentiment
6.9
Number of Reviews
45
Ranking in other categories
Data Warehouse (12th), Hadoop (7th)
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
Integrates diverse data sources and streamlines ETL processes effectively
Regarding potential areas of improvement for Azure Data Factory, there is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration. Azure Data Factory should consider how to enhance integration or filtering for more transformations, such as integrating with Spark clusters. I am satisfied with Azure Data Factory so far, but I suggest integrating some AI functionality to analyze data during the transition itself, providing insights such as null records, common records, and duplicates without running a separate pipeline or job. The monitoring tools in Azure Data Factory are helpful for optimizing data pipelines; while the current feature is adequate, they can improve by creating a live dashboard to see the online process, including how much percentage has been completed, which will be very helpful for people who are monitoring the pipeline.
Shiv Subramaniam Koduvayur - PeerSpot reviewer
Parallel data processing streamlines operations while cost and cloud integration challenge adoption
The cost of the solution is on the more expensive side, which is a concern for me. Additionally, its promotion and interaction with cloud applications are limited. The cloud version is only available in AWS, and in the Middle East, it is not well-developed in the Azure environment. For the cost to be reduced, it should match competitors. Many features need to be incorporated on the cloud.
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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…
 

Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Government
6%
Financial Services Firm
22%
Insurance Company
7%
Manufacturing Company
7%
Computer Software Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise55
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise5
Large Enterprise33
 

Questions from the Community

How do you select the right cloud ETL tool?
AWS Glue and Azure Data factory for ELT best performance cloud services.
How does Azure Data Factory compare with Informatica PowerCenter?
Azure Data Factory is flexible, modular, and works well. In terms of cost, it is not too pricey. It offers the stability and reliability I am looking for, good scalability, and is easy to set up an...
How does Azure Data Factory compare with Informatica Cloud Data Integration?
Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...
What needs improvement with IBM Netezza Performance Server?
The cost of the solution is on the more expensive side, which is a concern for me. Additionally, its promotion and interaction with cloud applications are limited. The cloud version is only availab...
What advice do you have for others considering IBM Netezza Performance Server?
The solution has generally received positive feedback from me and is recommended for continued use by end users. However, the product cost is high compared to others in the market, and this cost ha...
 

Also Known As

No data available
Netezza Performance Server, Netezza, Netezza Analytics
 

Overview

 

Sample Customers

1. Adobe 2. BMW 3. Coca-Cola 4. General Electric 5. Johnson & Johnson 6. LinkedIn 7. Mastercard 8. Nestle 9. Pfizer 10. Samsung 11. Siemens 12. Toyota 13. Unilever 14. Verizon 15. Walmart 16. Accenture 17. American Express 18. AT&T 19. Bank of America 20. Cisco 21. Deloitte 22. ExxonMobil 23. Ford 24. General Motors 25. IBM 26. JPMorgan Chase 27. Microsoft (Azure Data Factory is developed by Microsoft) 28. Oracle 29. Procter & Gamble 30. Salesforce 31. Shell 32. Visa
Seattle Childrens Hospital, Carphone Warehouse, Vanderbilt University School of Medicine, Battelle, Start Today Co. Ltd., Kelley Blue Book, Trident Marketing, Elisa Corporation, Catalina Marketing, iBasis, Barnes & Noble, Qualcomm, MediaMath, Acxiom, iBasis, Foxwoods
Find out what your peers are saying about Azure Data Factory vs. IBM Netezza Performance Server and other solutions. Updated: September 2025.
869,566 professionals have used our research since 2012.