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Azure Data Factory vs Oracle Big Data Appliance 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:
 

Categories and Ranking

Azure Data Factory
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
91
Ranking in other categories
Data Integration (1st), Cloud Data Warehouse (2nd)
Oracle Big Data Appliance
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
6
Ranking in other categories
Data Warehouse (13th)
 

Featured Reviews

Joy Maitra - PeerSpot reviewer
Facilitates seamless data pipeline creation with good analytics and and thorough monitoring
Azure Data Factory is a low code, no code platform, which is helpful. It provides many prebuilt functionalities that assist in building data pipelines. Also, it facilitates easy transformation with all required functionalities for analytics. Furthermore, it connects to different sources out-of-the-box, making integration much easier. The monitoring is very thorough, though a more readable version would be appreciable.
Mohammed Hamad - PeerSpot reviewer
Provides clean, centralized data
From a technical perspective, Big Data Appliance could be improved with more innovation in the AI and machine-learning parts instead of relying on Cloudera. Oracle could also improve Big Data Appliance by having one technology on their stack and working on it instead of continually changing the name or technologies or features. In addition, they could have a program to enable their partners to use this technology because right now, I have to have an expert to use the AI elements.

Quotes from Members

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

Pros

"An excellent tool for pipeline orchestration."
"I like the basic features like the data-based pipelines."
"The most valuable aspect is the copy capability."
"We have been using drivers to connect to various data sets and consume data."
"Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness."
"The most valuable features are data transformations."
"I like how you can create your own pipeline in your space and reuse those creations. You can collaborate with other people who want to use your code."
"We haven't had any issues connecting it to other products."
"The best thing about the product is that the end-user can build the reports by themselves without really knowing anything about databases."
"Because Big Data Appliance allows me to have a single source of truth, it means I have clean data that can be monetized and leveraged to gain more insights with real-time reports from the dashboard."
"This is a comprehensive solution that is easy to deploy."
 

Cons

"Real-time replication is required, and this is not a simple task."
"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."
"The initial setup is not very straightforward."
"Customer service is not satisfactory. Third-party personnel handle support and rely on a knowledge repository."
"While it has a range of connectors for various systems, such as ERP systems, the support for these connectors can be lacking."
"User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."
"Azure Data Factory uses many resources and has issues with parallel workflows."
"The thing we missed most was data update, but this is now available as of two weeks ago."
"It seems like the deployment of repositories has become more difficult in later versions of the product rather than easier."
"The product should be simplified for the average user."
"From a technical perspective, Big Data Appliance could be improved with more innovation in the AI and machine-learning parts instead of relying on Cloudera."
 

Pricing and Cost Advice

"My company is on a monthly subscription for Azure Data Factory, but it's more of a pay-as-you-go model where your monthly invoice depends on how many resources you use. On a scale of one to five, pricing for Azure Data Factory is a four. It's just the usage fees my company pays monthly."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"The pricing is a bit on the higher end."
"Data Factory is affordable."
"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."
"The price you pay is determined by how much you use it."
"The cost is based on the amount of data sets that we are ingesting."
"Data Factory is expensive."
"Oracle's prices are too high compared to others in the market."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Government
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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 Oracle Big Data Appliance?
Areas of Oracle Big Data Appliance that can be improved include the pricing perspective because nowadays they have competition. We have so many technologies that have come to the market for less th...
What is your primary use case for Oracle Big Data Appliance?
The typical use case for Oracle Big Data Appliance, which my clients use, is usually that the customer who has an Oracle application uses it because they can leverage the storage part. I don't need...
 

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
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Find out what your peers are saying about Azure Data Factory vs. Oracle Big Data Appliance and other solutions. Updated: July 2025.
865,384 professionals have used our research since 2012.