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Azure Data Factory vs Oracle Autonomous Data Warehouse comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 18, 2024

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
Ranking in Cloud Data Warehouse
2nd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
94
Ranking in other categories
Data Integration (3rd)
Oracle Autonomous Data Ware...
Ranking in Cloud Data Warehouse
12th
Average Rating
8.4
Reviews Sentiment
6.9
Number of Reviews
19
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of March 2026, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 5.4%, down from 8.5% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 5.7%, up from 4.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Mindshare Distribution
ProductMindshare (%)
Azure Data Factory5.4%
Oracle Autonomous Data Warehouse5.7%
Other88.9%
Cloud Data Warehouse
 

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.
Kwajah Mohiuddin - PeerSpot reviewer
Global Head of Architecture at a financial services firm with 1,001-5,000 employees
Provides self-repair features, but the setup is complex
We use the product for online applications. We use it in the financial industry The product has self-repair features. The tool tunes itself. It separates compute from storage. We can scale storage and compute separately. The setup is complex. Oracle is a complex tool. I have been using Oracle…

Quotes from Members

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

Pros

"It is beneficial that the solution is written with Spark as the back end."
"The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with."
"It makes it easy to collect data from different sources."
"For developers that are very accustomed to the Microsoft development studio, it's very easy for them to complete end-to-end data integration."
"Data Factory's best features are simplicity and flexibility."
"Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."
"The most valuable feature is the copy activity."
"The security of the agent that is installed on-premises is very good."
"The product is easy to use."
"The solution integrates well with Power BI."
"Self-patching and runs machine-learning across its logs all the time"
"It provides Transparent Data Encryption (TDE) capabilities by default to address data security issues."
"It is a stable and scalable solution."
"The analytics have been very good. We've found them to be quite useful."
"With Oracle Autonomous Data Warehouse, things are much simpler. Creating a structure, initializing the servers, extending the servers, those are all things that are very, very easy. That's the main reason we use it."
"A very good integration feature that restricts access to unauthorized people."
 

Cons

"Data Factory's monitorability could be better."
"They require more detailed error reporting, data normalization tools, easier connectivity to other services, more data services, and greater compatibility with other commonly used schemas."
"The Microsoft documentation is too complicated."
"We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on."
"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."
"The thing we missed most was data update, but this is now available as of two weeks ago."
"Some known bugs and issues with Azure Data Factory could be rectified."
"Data Factory's performance during heavy data processing isn't great."
"Sometimes the solution works differently between the cloud and on-premises. It needs to be more consistent and predictable."
"One of the major problem is creating custom tablespace. The ADB serverless option doesn't support custom tablespace creation, which could cause issues during on-premise database migration that requires specifically named tablespace. There should be an option to create customized tablespace."
"The solution could be improved by allowing for migration tools from other cloud services, including migration from Amazon Redshift, RDS, and Aurora."
"The initial setup was pretty complex. It was not easy."
"I would like to see an on-premise solution in the future."
"The installation process is complex. Oracle can make the installation process better."
"The setup is complex."
"We are not satisfied with the technical support. Their understanding is lacking."
 

Pricing and Cost Advice

"The licensing is a pay-as-you-go model, where you pay for what you consume."
"The price is fair."
"The solution is cheap."
"Data Factory is expensive."
"The licensing cost is included in the Synapse."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"I don't see a cost; it appears to be included in general support."
"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."
"Cloud solutions are cheaper, but in the long run, they may not be much cheaper. They certainly have a lower initial cost. The licensing is yearly, and it is based on the size of the hardware and the number of users."
"ROI is high."
"The solution's cost is reasonable."
"We pay approximately $70,000 per month. The cost includes maintenance and support."
"The price depends on the configuration we choose."
"You pay as you go, and you don't pay for services that you don't use."
"On a scale from one to ten, where one is a low price and ten is a high price, I rate the pricing an eight."
"The cost is perfect with Oracle Universal credit."
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
9%
Government
6%
Manufacturing Company
10%
Media Company
8%
Computer Software Company
8%
Insurance Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise20
Large Enterprise57
By reviewers
Company SizeCount
Small Business7
Midsize Enterprise1
Large Enterprise11
 

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 is your experience regarding pricing and costs for Oracle Autonomous Data Warehouse?
We pay approximately $70,000 per month. The cost includes maintenance and support.
What needs improvement with Oracle Autonomous Data Warehouse?
Optimization should be better. The SQLs are sometimes very slow. I also noticed that Java is not supported, which is not ideal.
What is your primary use case for Oracle Autonomous Data Warehouse?
We are using Oracle Autonomous Data Warehouse for analytics in my company.
 

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
Hertz, TaylorMade Golf, Outront Media, Kingold, FSmart, Drop-Tank
Find out what your peers are saying about Azure Data Factory vs. Oracle Autonomous Data Warehouse and other solutions. Updated: March 2026.
884,732 professionals have used our research since 2012.