Azure Data Factory vs Oracle Autonomous Data Warehouse comparison

Azure Data Factory vs. Oracle Autonomous Data Warehouse

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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

7th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Data Integration (5th)

Oracle Autonomous Data Ware...

Ranking in Cloud Data Warehouse

14th

Average Rating

8.4

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of September 2026, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 5.2%, down from 6.8% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 4.2%, down from 5.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	5.2%
Oracle Autonomous Data Warehouse	4.2%
Other	90.6%

Cloud Data Warehouse

Featured Reviews

Kunal Das

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.

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reviewer1297710

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…

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Quotes from Members

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

Pros

"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."

"It is very modular; it works well, is very flexible, and you can easily bring in outside capabilities and build any features you want."

"My only advice is that Azure Data Factory, particularly for data ingestion, is a good choice."

"The most valuable feature of Azure Data Factory is the core features that help you through the whole Azure pipeline or value chain."

"The security of the agent that is installed on-premises is very good."

"I think it makes it very easy to understand what data flow is and so on. You can leverage the user interface to do the different data flows, and it's great. I like it a lot."

"Azure Data Factory became more user-friendly when data-flows were introduced."

"Data Factory itself is great, it's pretty straightforward, you can easily add sources, join and lookup information, etc., and the ease of use is pretty good."

More Azure Data Factory pros

"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."

"It is a very stable tool...It is an extremely scalable tool."

"It provides Transparent Data Encryption (TDE) capabilities by default to address data security issues."

"The performance and scalability are awesome."

"The product is easy to use."

"The integration feature is very good because you can automate protection security automatically, restricting the access of unauthorized people."

"Oracle Autonomous Data Warehouse is used globally to deliver extreme performance on large Financial data sets."

"The solution has a self-backup, so you don't need a DBA (database administrator) to do a backup."

More Oracle Autonomous Data Warehouse pros

Cons

"The product could provide more ways to import and export data."

"I did not see any positive impact from Azure Data Factory overall."

"There's space for improvement in the development process of the data pipelines."

"There's no Oracle connector if you want to do transformation using data flow activity, so Azure Data Factory needs more connectors for data flow transformation."

"Technical support isn't the best, as it's a bit delayed at times. Whenever we need some urgent support, wherein we have to restart or something has stuck, it takes a bit of time."

"The inability to connect local VMs and local servers into the data flow is a limitation that prevents giving Azure Data Factory a perfect score."

"DataStage is easier to learn than Data Factory because it's more visual. Data Factory has some drag-and-drop options, but it's not as intuitive as DataStage. It would be better if they added more drag-and-drop features. You can start using DataStage without knowing the code. You don't need to learn how the code works before using the solution."

"It would be helpful if they could adjust the data capture feature so that when there are source-side changes ADF could automatically figure it out."

More Azure Data Factory cons

"Optimization should be better."

"An improvement for us would be the inclusion of support for an internal IP, so we could use it directly with the VCN in Oracle Cloud."

"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."

"It doesn't work well when you have unstructured data or you need online analytics. It is not as nice as Hadoop in these aspects."

"Ease of connectivity could be improved."

"Sometimes the solution works differently between the cloud and on-premises. It needs to be more consistent and predictable."

"It is very important the integration with other platforms be made to be as easy as it is with an on-premises deployment."

"Oracle Autonomous Data Warehouse is not available as an on-premises solution."

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"The price you pay is determined by how much you use it."

"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 is fair."

"The licensing cost is included in the Synapse."

"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."

"ADF is cheaper compared to AWS."

"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."

"This is a cost-effective solution."

More Azure Data Factory pricing and cost advice

"You pay as you go, and you don't pay for services that you don't use."

"The price depends on the configuration we choose."

"The cost is perfect with Oracle Universal credit."

"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."

"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."

"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."

"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."

More Oracle Autonomous Data Warehouse pricing and cost advice

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914,805 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

11%

Manufacturing Company

Computer Software Company

Construction Company

Financial Services Firm

11%

Media Company

10%

Outsourcing Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	21
Large Enterprise	64

By reviewers
Company Size	Count
Small Business	7
Midsize Enterprise	1
Large Enterprise	11

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.

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Compared 10% of the time

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Compared 9% of the time

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Compared 7% of the time

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Product Reports

Azure Data Factory

Download Azure Data Factory product report

Oracle Autonomous Data Warehouse

Download Oracle Autonomous Data Warehouse product report

Overview

Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.

Microsoft

Oracle Autonomous Data Warehouse is a cloud-based service offering advanced data management capabilities, including automated administration and high performance for analytics tasks. It is ideal for enterprises prioritizing security, easy maintenance, and dynamic scale.

Oracle Autonomous Data Warehouse stands out by offering self-managing capabilities that minimize administrative overhead, allowing organizations to focus on data-driven decision-making. With features such as transparent data encryption, seamless cloud integration, and automated query tuning, it ensures secure and efficient data operations. Its architecture separates compute and storage, enhancing scalability and performance. Despite its setup complexity and higher cost than some competitors, it offers deep integration with Oracle Database, ensuring reliable performance and fast data exchange.

What features define Oracle Autonomous Data Warehouse?

Self-Patching: Automatically updates to ensure security and performance.
Auto-Scaling: Dynamically adjusts resources to meet workload demands.
Query Tuning: Optimizes queries for better performance without user intervention.
Seamless Cloud Integration: Easily connects with Oracle and other cloud applications.
Transparent Data Encryption: Provides secure data handling to meet compliance needs.
Smart Scan: Efficiently processes queries to reduce data retrieval times.

What benefits can be expected from Oracle Autonomous Data Warehouse?

Cost-Effectiveness: Reduces operational costs through automation and serverless operations.
High Security: Ensures data protection with encryption and isolated resources.
Performance Enhancement: High-speed data processing and query response times.
Easy Maintenance: Minimal administrative tasks due to automation.
Scalability: Effortlessly scales resources to accommodate growth.

Oracle Autonomous Data Warehouse is widely used in finance, banking, transport, and manufacturing, supporting data analytics in financial systems, procurement, and student management. It facilitates large-scale transaction processing, offering centralized reporting and dynamic resource allocation, which is crucial for enhancing performance across industries.

Oracle

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

Azure Data Factory vs. Oracle Autonomous Data Warehouse