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

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.

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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

"I like how you can create your own pipeline in your space and reuse those creations. You can collaborate with other people who want to use your code."

"I value the integration capabilities with other platforms and software in Azure Data Factory the most."

"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."

"The flexibility that Azure Data Factory offers is great."

"From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connects and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature."

"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."

"Azure Data Factory is a low code, no code platform, which is helpful."

"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."

More Azure Data Factory pros

"The performance and scalability are awesome."

"The product is easy to use."

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

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

"The solution is used for analytics and it works for our data security needs."

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

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

"The solution is self-securing. All data is encrypted and security updates and patches are applied automatically both periodically and off-cycle."

More Oracle Autonomous Data Warehouse pros

Cons

"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."

"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."

"My only problem is the seamless connectivity with various other databases, for example, SAP."

"The solution can be improved by decreasing the warmup time which currently can take up to five minutes."

"It does not appear to be as rich as other ETL tools. It has very limited capabilities."

"The product's technical support has certain shortcomings, making it an area where improvements are required."

"The one element of the solution that we have used and could be improved is the user interface."

"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."

More Azure Data Factory cons

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

"The setup is complex."

"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."

"Ease of connectivity could be improved."

"Optimization should be better."

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

"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."

"A lot of the tools that were previously there have now been taken away."

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"The price is fair."

"This is a cost-effective solution."

"The solution is cheap."

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

"The solution's pricing is competitive."

"Data Factory is expensive."

"Data Factory is affordable."

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

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."

"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 price depends on the configuration we choose."

"ROI is high."

"We pay approximately $70,000 per month. The cost includes maintenance and support."

"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."

"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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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.

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.

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

Comparisons

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 24% of the time

Snowflake vs Oracle Autonomous Data Warehouse

Compared 17% of the time

Databricks vs Oracle Autonomous Data Warehouse

Compared 14% 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 6% of the time

More Oracle Autonomous Data Warehouse Competitors

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 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

Azure Data Factory vs. Oracle Autonomous Data Warehouse