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Azure Data Factory vs Oracle Data Integrator Cloud Service comparison

 

Comparison Buyer's Guide

Executive Summary

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
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
91
Ranking in other categories
Data Integration (1st), Cloud Data Warehouse (2nd)
Oracle Data Integrator Clou...
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
7
Ranking in other categories
Cloud Data Integration (20th)
 

Mindshare comparison

While both are Data Integration and Access solutions, they serve different purposes. Azure Data Factory is designed for Data Integration and holds a mindshare of 7.9%, down 12.2% compared to last year.
Oracle Data Integrator Cloud Service, on the other hand, focuses on Cloud Data Integration, holds 0.4% mindshare, up 0.2% since last year.
Data Integration
Cloud Data Integration
 

Featured Reviews

Joy Maitra - PeerSpot reviewer
Facilitates seamless data pipeline creation with good analytics and and thorough monitoring
Azure Data Factory is a low code, no code platform, which is helpful. It provides many prebuilt functionalities that assist in building data pipelines. Also, it facilitates easy transformation with all required functionalities for analytics. Furthermore, it connects to different sources out-of-the-box, making integration much easier. The monitoring is very thorough, though a more readable version would be appreciable.
Peeyush Chouksey - PeerSpot reviewer
Allows us to integrate different cloud services with different applications
It's lacking a lot of mapping features that Oracle OSB and SOA have. It needs to evolve a lot. When it comes to mapping, you are quite restricted. If you have to use a specific, typical function, you need to do a Java callout or something. OSB has a lot of features they are using like Java APIs because it's on-premises.

Quotes from Members

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

Pros

"It is easy to integrate."
"The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with."
"The most valuable aspect is the copy capability."
"Most of our customers are Microsoft shops and prefer Azure Data Factory because they have good licensing options and a trust factor with Microsoft."
"It is easy to deploy workflows and schedule jobs."
"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."
"I like the basic features like the data-based pipelines."
"The data is more scalable."
"It's on the cloud, so it's scalable and quite easy to work with."
"Oracle Data Integrator helps us build tables and data marts and allows us to schedule them daily, for nearly real-time data warehousing."
"The data is stored in the cloud, making it easy to download data simultaneously into multiple smaller servers, effectively downsizing the process."
"The solution is easy to manage and offers good integration. You can run all the tasks one by one which is really helpful, and pick the day and time to do so."
"Oracle integration cloud has got the adapters for all their products, which makes integration faster."
"Having a single vendor supporting the entire suite of applications."
"The most valuable thing to me is its simplicity. A person with zero knowledge can also develop the integration without having extensive technology knowledgebase. They can also work on creating their own integration."
 

Cons

"The main challenge with implementing Azure Data Factory is that it processes data in batches, not near real-time. To achieve near real-time processing, we need to schedule updates more frequently, which can be an issue. Its interface needs to be lighter."
"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"There is no built-in pipeline exit activity when encountering an error."
"I do not have any notes for improvement."
"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."
"Areas for improvement in Azure Data Factory include connectivity and integration. When you use integration runtime, whenever there's a failure, the backup process in Azure Data Factory takes time, so this is another area for improvement."
"There are performance issues, particularly with the underlying compute, which should be configurable."
"If the user interface was more user friendly and there was better error feedback, it would be helpful."
"I would like to see different cloud adapters or connectors in case of integration. When you have Oracle to Oracle, they are good. They have really good connectors, but if it is a different ERP, like Obsidian, that is where they are faced with problems in OIC."
"I've found technical support not very effective. They should work to improve their services."
"It can be made much easier for users. They should be allowed to easily monitor the data extraction and flow, allowing them to observe real-time data flow within the software, making the process straightforward."
"It's lacking a lot of mapping features that Oracle OSB and SOA have. It needs to evolve a lot."
"The pricing could be more competitive."
"This is an expensive solution compared to other products on the market."
"Bulk uploading can be a problem when you hit the upper limit."
 

Pricing and Cost Advice

"Data Factory is affordable."
"The solution's pricing is competitive."
"ADF is cheaper compared to AWS."
"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 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."
"The price is fair."
"It's not particularly expensive."
"The price is competitive compared to Boomi which is much higher."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Government
6%
No data available
 

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 Data Integrator Cloud Service?
The data is stored in the cloud, making it easy to download data simultaneously into multiple smaller servers, effectively downsizing the process.
What needs improvement with Oracle Data Integrator Cloud Service?
It can be made much easier for users. They should be allowed to easily monitor the data extraction and flow, allowing them to observe real-time data flow within the software, making the process str...
What is your primary use case for Oracle Data Integrator Cloud Service?
I have experience working with Korean Telecom (Katie) on various projects involving data integration, especially with Oracle databases. These projects included tasks such as data collection, ETL (E...
 

Overview

 

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
Amplifon
Find out what your peers are saying about Azure Data Factory vs. Oracle Data Integrator Cloud Service and other solutions. Updated: May 2023.
861,390 professionals have used our research since 2012.