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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
6.9
Number of Reviews
92
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

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.
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

"The most valuable aspect is the copy capability."
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."
"Feature-wise, one of the most valuable ones is the data flows introduced recently in the solution."
"The solution has a good interface and the integration with GitHub is very useful."
"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."
"The tool's most valuable features are its connectors. It has many out-of-the-box connectors. We use ADF for ETL processes. Our main use case involves integrating data from various databases, processing it, and loading it into the target database. ADF plays a crucial role in orchestrating these ETL workflows."
"UI is easy to navigate and I can retrieve VTL code without knowing in-depth coding languages."
"Allows more data between on-premises and cloud solutions"
"This is a comprehensive solution that is easy to deploy."
"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."
"The best thing about the product is that the end-user can build the reports by themselves without really knowing anything about databases."
 

Cons

"Some prebuilt data source or data connection aspects are generic."
"We require Azure Data Factory to be able to connect to Google Analytics."
"Currently, smaller businesses face a disadvantage in terms of pricing, and reducing costs could address this issue."
"We have experienced some issues with the integration. This is an area that needs improvement."
"I have not found any real shortcomings within the product."
"The setup and configuration process could be simplified."
"My only problem is the seamless connectivity with various other databases, for example, SAP."
"The user interface could use improvement. It's not a major issue but it's something that can be improved."
"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."
"It seems like the deployment of repositories has become more difficult in later versions of the product rather than easier."
 

Pricing and Cost Advice

"This is a cost-effective solution."
"Understanding the pricing model for Data Factory is quite complex."
"Pricing appears to be reasonable in my opinion."
"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"The price is fair."
"Azure Data Factory gives better value for the price than other solutions such as Informatica."
"I would not say that this product is overly 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
13%
Computer Software Company
12%
Manufacturing Company
9%
Government
6%
No data available
 

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 Business1
Midsize Enterprise1
Large Enterprise6
 

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: September 2025.
869,566 professionals have used our research since 2012.