Azure Data Factory vs Oracle Autonomous Data Warehouse comparison

Microsoft and Oracle are both solutions in the Cloud Data Warehouse category. Microsoft is ranked #2 with an average rating of 8.2, while Oracle is ranked #11 with an average rating of 7.7. Microsoft holds a 5.7% mindshare in CDW, compared to Oracle’s 5.7% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 95% of Oracle users who would recommend it.

Azure Data Factory

Read 93 Azure Data Factory reviews

11,065 Views
1,770 Comparison Views

92% willing to recommend

Oracle Autonomous Data Ware...

Read 19 Oracle Autonomous Data Warehouse reviews

2,219 Views
1,664 Comparison Views

95% willing to recommend

Azure Data Factory

Oracle Autonomous Data Ware...

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Dec 18, 2024

Azure Data Factory and Oracle Autonomous Data Warehouse compete in the data management space. Azure Data Factory seems to have the upper hand with its integration capabilities and flexibility, while Oracle Autonomous Data Warehouse is notable for its automation and performance.

Features: Azure Data Factory offers data integration, built-in connectors for various sources, and a user-friendly drag-and-drop interface for creating data pipelines. It integrates well with Azure services and supports GitHub for data flow management. Oracle Autonomous Data Warehouse features self-patching, tuning, and scaling, reducing administrative work. It includes robust security and machine learning for seamless data management.

Room for Improvement: Azure Data Factory could enhance integration with Azure services, improve scheduling features, and offer better big data capabilities. Users request more connectors for systems like SAP and Oracle, as well as improved error feedback and pricing models. Oracle Autonomous Data Warehouse users seek better data migration support, storage flexibility, and an improved user interface for data mining and machine learning tasks, as well as better interconnectivity and documentation.

Ease of Deployment and Customer Service: Azure Data Factory is deployed on the public cloud, offering scalability with strong community support, though direct support can vary. Oracle Autonomous Data Warehouse offers public, private, and on-premises deployments, with responsive technical support, though some users desire more comprehensive options.

Pricing and ROI: Azure Data Factory uses a pay-as-you-go model, seen as cost-effective for data projects but posing challenges in cost prediction. Oracle Autonomous Data Warehouse is perceived as more expensive due to its features and automation, with trial offerings suggesting potential ROI through reduced infrastructure costs and improved data management.

To learn more, read our detailed Azure Data Factory vs. Oracle Autonomous Data Warehouse Report (Updated: February 2026).

Buyer's Guide

Azure Data Factory vs. Oracle Autonomous Data Warehouse

February 2026

Download the complete report

Helped 882,260 peers since 2012

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

Ranking in other categories

Data Integration (3rd)

Oracle Autonomous Data Ware...

Ranking in Cloud Data Warehouse

11th

Average Rating

8.4

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of February 2026, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 5.7%, down from 9.0% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 5.7%, up from 4.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Market Share Distribution
Product	Market Share (%)
Azure Data Factory	5.7%
Oracle Autonomous Data Warehouse	5.7%
Other	88.6%

Cloud Data Warehouse

Featured Reviews

KandaswamyMuthukrishnan

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.

Read full review

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…

Read full review

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 feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."

"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."

"It is beneficial that the solution is written with Spark as the back end."

"Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."

"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."

"The most valuable aspect is the copy capability."

"The solution can scale very easily."

"I like its integration with SQL pools, its ability to work with Databricks, its pipelines, and the serverless architecture are the most effective features."

More Azure Data Factory pros

"I really like the auto-tuning, auto-scaling, and the automatic load balancing and query tuning in the system."

"A very good integration feature that restricts access to unauthorized people."

"The product is easy to use."

"It is a stable and scalable solution."

"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."

"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."

"Self-patching and runs machine-learning across its logs all the time"

More Oracle Autonomous Data Warehouse pros

Cons

"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."

"Data Factory could be improved in terms of data transformations by adding more metadata extractions."

"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."

"Azure Data Factory can improve by having support in the drivers for change data capture."

"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."

"Data Factory has so many features that it can be a little difficult or confusing to find some settings and configurations. I'm sure there's a way to make it a little easier to navigate."

"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."

"Some of the optimization techniques are not scalable."

More Azure Data Factory cons

"The solution could be improved by allowing for migration tools from other cloud services, including migration from Amazon Redshift, RDS, and Aurora."

"I would like to see an on-premise solution in the future."

"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."

"The solution lacks visibility options."

"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."

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

"They should make the solution more user-friendly."

"Ease of connectivity could be improved."

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."

"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."

"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."

"ADF is cheaper compared to AWS."

"Pricing appears to be reasonable in my opinion."

"Data Factory is expensive."

"I would rate Data Factory's pricing nine out of ten."

"Azure Data Factory gives better value for the price than other solutions such as Informatica."

More Azure Data Factory pricing and cost advice

"Oracle Autonomous Data Warehouse's pricing is fair and reasonable compared to the other cloud vendors."

"The price depends on the configuration we choose."

"The solution is expensive."

"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."

"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."

"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 solution's cost is reasonable."

More Oracle Autonomous Data Warehouse pricing and cost advice

See which vendors are best for you

Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.

See recommendations

882,260 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

12%

Computer Software Company

11%

Manufacturing Company

Government

Manufacturing Company

10%

Media Company

Computer Software Company

Insurance Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	19
Large Enterprise	57

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.

See all answers

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...

See all answers

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...

See all answers

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.

See all answers

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.

See all answers

What is your primary use case for Oracle Autonomous Data Warehouse?

We are using Oracle Autonomous Data Warehouse for analytics in my company.

See all answers

Comparisons

Informatica Intelligent Data Management Cloud (IDMC) vs Azure Data Factory

Compared 6% of the time

Snowflake vs Azure Data Factory

Compared 6% of the time

FME vs Azure Data Factory

Compared 4% of the time

Palantir Foundry vs Azure Data Factory

Compared 4% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 4% of the time

More Azure Data Factory Competitors

BigQuery vs Oracle Autonomous Data Warehouse

Compared 25% of the time

Snowflake vs Oracle Autonomous Data Warehouse

Compared 17% of the time

Databricks vs Oracle Autonomous Data Warehouse

Compared 15% of the time

Microsoft Azure Synapse Analytics vs Oracle Autonomous Data Warehouse

Compared 10% of the time

Amazon Redshift vs Oracle Autonomous Data Warehouse

Compared 7% of the time

More Oracle Autonomous Data Warehouse Competitors

Product Reports

Buyer's Guide

Azure Data Factory

February 2026

Download Azure Data Factory product report

Buyer's Guide

Oracle Autonomous Data Warehouse

January 2026

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 the world’s first and only autonomous database optimized for analytic workloads, including data marts, data warehouses, data lakes, and data lakehouses. With Autonomous Data Warehouse, data scientists, business analysts, and nonexperts can rapidly, easily, and cost-effectively discover business insights using data of any size and type. Built for the cloud and optimized using Oracle Exadata, Autonomous Data Warehouse benefits from faster performance and, according to an IDC report (PDF), lowers operational costs by an average of 63%.

Autonomous Database provides the foundation for a data lakehouse—a modern, open architecture that enables you to store, analyze, and understand all your data. The data lakehouse combines the power and richness of data warehouses with the breadth, flexibility, and low cost of popular open source data lake technologies. Access your data lakehouse through Autonomous Database using the world's most powerful and open SQL processing engine.

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

Buyer's Guide

Azure Data Factory vs. Oracle Autonomous Data Warehouse

February 2026

Free Report: Azure Data Factory vs. Oracle Autonomous Data Warehouse

Find out what your peers are saying about Azure Data Factory vs. Oracle Autonomous Data Warehouse and other solutions. Updated: February 2026.

DOWNLOAD NOW

882,260 professionals have used our research since 2012.

See our Azure Data Factory vs. Oracle Autonomous Data Warehouse report.

See our list of best Cloud Data Warehouse vendors.

We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.