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 #12 with an average rating of 7.6. Microsoft holds a 6.8% mindshare in CDW, compared to Oracle’s 5.2% 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 92 Azure Data Factory reviews

13,131 Views
2,232 Comparison Views

92% willing to recommend

Oracle Autonomous Data Ware...

Read 19 Oracle Autonomous Data Warehouse reviews

1,988 Views
1,511 Comparison Views

95% willing to recommend

Azure Data Factory

Oracle Autonomous Data Ware...

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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: September 2025).

Buyer's Guide

Azure Data Factory vs. Oracle Autonomous Data Warehouse

September 2025

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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

2nd

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Integration (1st)

Oracle Autonomous Data Ware...

Ranking in Cloud Data Warehouse

12th

Average Rating

8.4

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of October 2025, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 6.8%, down from 9.4% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 5.2%, up from 4.3% 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	6.8%
Oracle Autonomous Data Warehouse	5.2%
Other	88.0%

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.

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Kwajah Mohiuddin

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…

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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

"An excellent tool for pipeline orchestration."

"This solution will allow the organisation to improve its existing data offerings over time by adding predictive analytics, data sharing via APIs and other enhancements readily."

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

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

"The function of the solution is great."

"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."

"On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good."

"I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets."

More Azure Data Factory pros

"It is an extremely scalable solution since you can dynamically change the resources as some other cloud solutions."

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

"The product has self-repair features."

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

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

"It is a stable and scalable solution."

"The analytics have been very good. We've found them to be quite useful."

"The product is easy to use."

More Oracle Autonomous Data Warehouse pros

Cons

"Some prebuilt data source or data connection aspects are generic."

"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."

"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."

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

"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."

"There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base."

"The speed and performance need to be improved."

"I have not found any real shortcomings within the product."

More Azure Data Factory cons

"There is a need for more storage to be allocated, but over a period of time, it becomes impossible to reduce it after using it."

"My main suggestion for Oracle is the configuration and key values that come for JSON files. When we create a table, especially if you see in our RedShift or some other stuff, if I create a table on top of a JSON file with multiple array columns or superset columns, those column values create some difficulty in Oracle."

"Ease of connectivity could be improved."

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

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

"We are not satisfied with the technical support. Their understanding is lacking."

"The setup is complex."

"The initial setup was pretty complex. It was not easy."

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

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

"Pricing is comparable, it's somewhere in the middle."

"Data Factory is affordable."

"Our licensing fees are approximately 15,000 ($150 USD) per month."

"Azure products generally offer competitive pricing, suitable for diverse budget considerations."

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

"The cost is based on the amount of data sets that we are ingesting."

"The licensing cost is included in the Synapse."

More Azure Data Factory pricing and cost advice

"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 solution's cost is reasonable."

"The solution is expensive."

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

"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."

"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."

"The cost is perfect with Oracle Universal credit."

More Oracle Autonomous Data Warehouse pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

Government

Computer Software Company

10%

Manufacturing Company

University

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	55

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...

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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 do you like most about Oracle Autonomous Data Warehouse?

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...

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

Comparisons

Snowflake vs Azure Data Factory

Compared 8% of the time

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

Compared 6% of the time

Informatica PowerCenter vs Azure Data Factory

Compared 6% of the time

FME vs Azure Data Factory

Compared 5% of the time

Palantir Foundry vs Azure Data Factory

Compared 5% of the time

More Azure Data Factory Competitors

BigQuery vs Oracle Autonomous Data Warehouse

Compared 31% of the time

Microsoft Azure Synapse Analytics vs Oracle Autonomous Data Warehouse

Compared 20% of the time

Snowflake vs Oracle Autonomous Data Warehouse

Compared 13% of the time

Oracle Exadata vs Oracle Autonomous Data Warehouse

Compared 10% of the time

Databricks vs Oracle Autonomous Data Warehouse

Compared 9% of the time

More Oracle Autonomous Data Warehouse Competitors

Product Reports

Buyer's Guide

Azure Data Factory

October 2025

Download Azure Data Factory product report

Buyer's Guide

Oracle Autonomous Data Warehouse

September 2025

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

September 2025

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