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Azure Data Factory vs Oracle Autonomous Data Warehouse comparison

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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
6th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
97
Ranking in other categories
Data Integration (6th)
Oracle Autonomous Data Ware...
Ranking in Cloud Data Warehouse
14th
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 October 2026, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 5.1%, down from 6.7% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 4.2%, down from 5.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Mindshare Distribution
ProductMindshare (%)
Azure Data Factory5.1%
Oracle Autonomous Data Warehouse4.2%
Other90.7%
Cloud Data Warehouse
 

Featured Reviews

Kunal Das - PeerSpot reviewer
Test Engineer at Happiest Minds Technologies
Drag-and-drop pipelines have saved days of work and now automate data movement and backfilling
If the AI features were more improved so that I don't have to provide each and every detail, Azure Data Factory could be improved in a much better way by improving the AI features. For example, if I want to fetch any data from a raw source, I need to provide each and every detail. But if I am just uploading my raw data and if AI will sync with that data, it can analyze that data and give me proper suggestions on how that should be done in a proper way. Automatic suggestions could improve in a much better way. As I have mentioned, the AI features as well as more drag-and-drop activities could be improved. If I am making a pipeline, it should give me suggestions, such as which activity should be used, so that I don't have to remember each activity. If I have used one activity, I shouldn't have to remember what activity should I use next. It should give auto-suggestions. That is why I have given a nine out of 10. Currently, I don't know about its governance and security, but in view of its improvement, I think Azure Data Factory should improve in these areas. As I already mentioned, the AI features should be improved. Also, the auto-suggestion features should also improve.
reviewer1297710 - PeerSpot reviewer
IT Administrator at a manufacturing company with 1,001-5,000 employees
Analytics and data security needs are met but optimization requires improvement
We are using Oracle Autonomous Data Warehouse for analytics in my company The solution is used for analytics and it works for our data security needs. We continue to use it with satisfaction. Optimization should be better. The SQLs are sometimes very slow. I also noticed that Java is not…

Quotes from Members

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

Pros

"Microsoft's technical support is responsive and quick to help."
"The security of the agent that is installed on-premises is very good."
"One advantage of Azure Data Factory is that it's fast, unlike SSIS and other on-premise tools. It's also very convenient because it has multiple connectors. The availability of native connectors allows you to connect to several resources to analyze data streams."
"Its integrability with the rest of the activities on Azure is most valuable."
"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."
"The feature I found most helpful in Azure Data Factory is the pipeline feature, including being able to connect to different sources. Azure Data Factory also has built-in security, which is another valuable feature."
"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."
"I enjoy the ease of use for the backend JSON generator, the deployment solution, and the template management."
"It is a stable and scalable solution."
"It provides Transparent Data Encryption (TDE) capabilities by default to address data security issues."
"It is a very stable tool...It is an extremely scalable tool."
"I highly recommend it for companies who want to test their application functionality, dev, or test DBs for cost optimization."
"I loved the simplicity of loading the data and simply relying on the self-tuning capabilities of ADW."
"The solution is used for analytics and it works for our data security needs."
"I like the fact that the solution is self-patching, that it's running machine-learning generally across its logs all the time in order to identify any issues and to self-repair."
"The product has self-repair features."
 

Cons

"The product's technical support has certain shortcomings, making it an area where improvements are required."
"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."
"There is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration."
"We have experienced some issues with the integration. This is an area that needs improvement."
"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."
"There is room for improvement primarily in its streaming capabilities. For structured streaming and machine learning model implementation within an ETL process, it lags behind tools like Informatica."
"Lacks in-built streaming data processing."
"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"A lot of the tools that were previously there have now been taken away."
"Oracle should increase visibility options because what's available now is limited."
"I would like to see Application Express and Oracle R Enterprise fully supported, and I would like to see Oracle Data Mining supported as a front end."
"The setup is complex."
"Sometimes the solution works differently between the cloud and on-premises. It needs to be more consistent and predictable."
"Optimization should be better."
"They should make the solution more user-friendly."
"I would like to see an on-premise solution in the future."
 

Pricing and Cost Advice

"The price you pay is determined by how much you use it."
"Azure products generally offer competitive pricing, suitable for diverse budget considerations."
"I don't see a cost; it appears to be included in general support."
"I would rate Data Factory's pricing nine out of ten."
"Pricing is comparable, it's somewhere in the middle."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"Product is priced at the market standard."
"Oracle Autonomous Data Warehouse's pricing is fair and reasonable compared to the other cloud vendors."
"In terms of architecture and pricing structure, I feel it is a little bit costly compared to Azure. It's fine compared to RedShift, but compared to Azure, it's a bit pricey when you calculate for one TB storage plus around five hours of reporting with the frequency of 1TB data. The cost adds up, making Oracle a bit expensive."
"The price depends on the configuration we choose."
"The licensing cost of the product can vary since you can integrate it very easily with other products or other cloud products...You pay as you use it, so it is not yearly or monthly payments to be made toward Oracle."
"We pay approximately $70,000 per month. The cost includes maintenance and support."
"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."
"ROI is high."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
11%
Manufacturing Company
9%
Computer Software Company
7%
Outsourcing Company
7%
Financial Services Firm
12%
Media Company
10%
Manufacturing Company
8%
Outsourcing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise64
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: September 2026.
918,614 professionals have used our research since 2012.