Azure Data Factory vs Oracle Autonomous Data Warehouse comparison

Azure Data Factory vs. Oracle Autonomous Data Warehouse

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Categories and Ranking

Azure Data Factory

Ranking in Cloud Data Warehouse

3rd

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

9th

Average Rating

8.6

Reviews Sentiment

7.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of December 2024, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 12.8%, down from 13.4% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 6.3%, up from 4.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse

Featured Reviews

Thulani David Mngadi

Data architect at Old Mutual

Data flow feature is valuable for data transformation tasks

The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem.

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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

"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."

"It makes it easy to collect data from different sources."

"I am one hundred percent happy with the stability."

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

"We have found the bulk load feature very valuable."

"The data mapping and the ability to systematically derive data are nice features. It worked really well for the solution we had. It is visual, and it did the transformation as we wanted."

"In terms of my personal experience, it works fine."

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

More Azure Data Factory pros

"The product has self-repair features."

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

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

"The performance and scalability are awesome."

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

"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."

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

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

More Oracle Autonomous Data Warehouse pros

Cons

"The pricing scheme is very complex and difficult to understand."

"The solution needs to integrate more with other providers and should have a closer integration with Oracle BI."

"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."

"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 deployment should be easier."

"When we initiated the cluster, it took some time to start the process."

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

"The thing we missed most was data update, but this is now available as of two weeks ago."

More Azure Data Factory cons

"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."

"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."

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

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

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

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

"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."

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"I would not say that this product is overly expensive."

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

"Pricing appears to be reasonable in my opinion."

"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."

"It's not particularly expensive."

"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."

"ADF is cheaper compared to AWS."

"My company is on a monthly subscription for Azure Data Factory, but it's more of a pay-as-you-go model where your monthly invoice depends on how many resources you use. On a scale of one to five, pricing for Azure Data Factory is a four. It's just the usage fees my company pays monthly."

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."

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

"The price depends on the configuration we choose."

"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."

"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."

"ROI is high."

"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 solution's cost is reasonable."

More Oracle Autonomous Data Warehouse pricing and cost advice

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824,067 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

Educational Organization

50%

Financial Services Firm

Computer Software Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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 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...

What is your experience regarding pricing and costs for Oracle Autonomous Data Warehouse?

The solution is expensive. I rate the price an eight out of ten.

What needs improvement with Oracle Autonomous Data Warehouse?

The setup is complex. Oracle is a complex tool.

Informatica PowerCenter vs Azure Data Factory

Comparisons

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Snowflake vs Azure Data Factory

Compared 10% of the time

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

Compared 8% of the time

Alteryx Designer vs Azure Data Factory

Compared 7% of the time

IBM InfoSphere DataStage vs Azure Data Factory

Compared 4% of the time

More Azure Data Factory Competitors

Snowflake vs Oracle Autonomous Data Warehouse

Compared 29% of the time

Microsoft Azure Synapse Analytics vs Oracle Autonomous Data Warehouse

Compared 21% of the time

Oracle Exadata vs Oracle Autonomous Data Warehouse

Compared 21% of the time

BigQuery vs Oracle Autonomous Data Warehouse

Compared 17% of the time

Amazon Redshift vs Oracle Autonomous Data Warehouse

Compared 3% 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

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Microsoft

Oracle

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.

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.

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