No more typing reviews! Try our Samantha, our new voice AI agent.

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
5.5
Users praise Azure Data Factory for improved ROI through cost savings, enhanced integration, and increased operational efficiency and satisfaction.
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.
Data Engineer at Vthinktechnologies
 

Customer Service

Sentiment score
6.3
Azure Data Factory support is mixed; praised for responsiveness and documentation, but some find it slow and inadequate.
Sentiment score
6.4
IBM Netezza Performance Server praised for knowledgeable support; mixed feedback on resolution speed post-acquisition, yet communication remains consistent.
On a scale of one to ten, I would rate the technical support as nine.
Senior Consultant Oracle Technologies at a tech vendor with 10,001+ employees
The technical support from Microsoft is rated an eight out of ten.
Chief Analytics Officer at Idiro Analytics
The technical support is responsive and helpful
Sr. Technical Architect at Hexaware Technologies Limited
Technical support is very costly for me, accounting for twenty-five to thirty percent of the product cost.
Project Manager at MAF Retail
 

Scalability Issues

Sentiment score
7.4
Azure Data Factory is praised for its scalability and flexibility, despite some integration issues in older tiers.
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.
Chief Analytics Officer at Idiro Analytics
I did not experience scalability issues.
Principal Data Engineer at Oracle
It is provided as a pre-configured box, and scaling is not an option.
Project Manager at MAF Retail
 

Stability Issues

Sentiment score
7.7
Azure Data Factory is stable and dependable, despite occasional connection issues and challenges with SQL query optimization.
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.
Chief Analytics Officer at Idiro Analytics
I have been using Azure Data Factory for a very long time, and I did not find too many issues.
Principal Data Engineer at Oracle
 

Room For Improvement

Azure Data Factory users experience setup complexity, connectivity issues, and seek improved performance, automation, and integration with other platforms.
IBM Netezza struggles with scalability, user interface, query performance, big data support, and high costs, needing better tools and integration.
The ability to handle the largest volumes of data is another concern; if I have to manage more than one terabyte of data every day, I am not comfortable dealing with Azure Data Factory and had to switch to Oracle Data Integrators (ODI) because it lacks performance features.
Senior Consultant Oracle Technologies at a tech vendor with 10,001+ employees
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
Chief Analytics Officer at Idiro Analytics
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
Sr. Technical Architect at Hexaware Technologies Limited
The cloud version is only available in AWS, and in the Middle East, it is not well-developed in the Azure environment.
Project Manager at MAF Retail
 

Setup Cost

Azure Data Factory provides cost-effective, usage-based pricing suitable for various budgets, with expenses depending on data volume and services.
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.
Chief Analytics Officer at Idiro Analytics
It is considered cost-effective.
Sr. Technical Architect at Hexaware Technologies Limited
 

Valuable Features

Azure Data Factory offers scalable ETL solutions with user-friendly interface, seamless Azure integration, robust orchestration, and effective dataset handling.
IBM Netezza Performance Server delivers fast analytics, ease of use, robust support, and efficient data warehousing with minimal maintenance.
It connects to different sources out-of-the-box, making integration much easier.
Sr. Technical Architect at Hexaware Technologies Limited
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
Data Engineer at Vthinktechnologies
Regarding the integration feature in Azure Data Factory, the integration part is excellent; we have major source connectors, so we can integrate the data from different data sources and also perform basic transformation while transforming, which is a great feature in Azure Data Factory.
Director at a computer software company with 1,001-5,000 employees
It operates as a high-speed data warehouse, which is essential for handling big data.
Project Manager at MAF Retail
 

Categories and Ranking

Azure Data Factory
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
96
Ranking in other categories
Data Integration (5th), Cloud Data Warehouse (7th)
IBM Netezza Performance Server
Average Rating
7.8
Reviews Sentiment
6.9
Number of Reviews
45
Ranking in other categories
Data Warehouse (12th), Hadoop (6th)
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
Director at a computer software company with 1,001-5,000 employees
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
Project Manager at MAF Retail
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.
report
Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.
902,988 professionals have used our research since 2012.
 

Comparison Review

it_user232068 - PeerSpot reviewer
Senior Data Architect at a pharma/biotech company with 1,001-5,000 employees
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
12%
Computer Software Company
9%
Manufacturing Company
9%
Construction Company
6%
Financial Services Firm
19%
Manufacturing Company
11%
Construction Company
10%
Comms Service Provider
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise63
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise6
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 Snowflake Computing, Teradata, Google and others in Cloud Data Warehouse. Updated: June 2026.
902,988 professionals have used our research since 2012.