No more typing reviews! Try our Samantha, our new voice AI agent.

Azure Data Factory vs Oracle Data Integrator Cloud Service comparison

Why PeerSpot?
 

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
6.7
Number of Reviews
97
Ranking in other categories
Data Integration (5th), Cloud Data Warehouse (7th)
Oracle Data Integrator Clou...
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
7
Ranking in other categories
Cloud Data Integration (31st)
 

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 2.2%, down 5.5% compared to last year.
Oracle Data Integrator Cloud Service, on the other hand, focuses on Cloud Data Integration, holds 1.2% mindshare, up 0.6% since last year.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.2%
Informatica Intelligent Data Management Cloud (IDMC)3.7%
SSIS3.6%
Other90.5%
Data Integration
Cloud Data Integration Mindshare Distribution
ProductMindshare (%)
Oracle Data Integrator Cloud Service1.2%
AWS Glue7.7%
AWS Database Migration Service6.9%
Other84.2%
Cloud Data Integration
 

Featured Reviews

Kunal Das - PeerSpot reviewer
Test Engineer at Happiest Minds Technologies
Drag-and-drop pipelines have saved days of work and now automate data movement and backfilling
If the AI features were more improved so that I don't have to provide each and every detail, Azure Data Factory could be improved in a much better way by improving the AI features. For example, if I want to fetch any data from a raw source, I need to provide each and every detail. But if I am just uploading my raw data and if AI will sync with that data, it can analyze that data and give me proper suggestions on how that should be done in a proper way. Automatic suggestions could improve in a much better way. As I have mentioned, the AI features as well as more drag-and-drop activities could be improved. If I am making a pipeline, it should give me suggestions, such as which activity should be used, so that I don't have to remember each activity. If I have used one activity, I shouldn't have to remember what activity should I use next. It should give auto-suggestions. That is why I have given a nine out of 10. Currently, I don't know about its governance and security, but in view of its improvement, I think Azure Data Factory should improve in these areas. As I already mentioned, the AI features should be improved. Also, the auto-suggestion features should also improve.
AD
Senior Solution Architect at a financial services firm with 10,001+ employees
A well-established product that meets all our specifications in terms of usability
In the initial stage when we went with Data Integrator Cloud Service it was primarily the nativity factor that was key for us. Having a single vendor supporting the entire suite of applications, and the ability to configure activities and direct integration with various other Oracle products, were the main attractive features within ODI. This is a well-established product that's good to have if you hold an Oracle suite of applications. It meets all our specifications in terms of usability.

Quotes from Members

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

Pros

"It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory."
"The solution can scale very easily."
"The most important feature is that it can help you do the multi-threading concepts."
"Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness."
"The data copy template is a valuable feature."
"I find that the solution integrates well with cloud technologies, which we are using for different clouds like Snowflake and AWS."
"What I like best about Azure Data Factory is that it allows you to create pipelines, specifically ETL pipelines. I also like that Azure Data Factory has connectors and solves most of my company's problems."
"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."
"The data is stored in the cloud, making it easy to download data simultaneously into multiple smaller servers, effectively downsizing the process."
"This is a well-established product that's good to have if you hold an Oracle suite of applications."
"Oracle integration cloud has got the adapters for all their products, which makes the integration a little faster and makes it easier to implement the integration quickly."
"It's on the cloud, so it's scalable and quite easy to work with."
"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."
"The solution is very stable and it's great once you get it working correctly."
"Oracle Data Integrator helps us build tables and data marts and allows us to schedule them daily, for nearly real-time data warehousing."
 

Cons

"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"There should be a way that it can do switches, so if at any point in time I want to do some hybrid mode of making any data collections or ingestions, I can just click on a button."
"Azure Data Factory uses many resources and has issues with parallel workflows."
"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."
"The performance could be better. It would be better if Azure Data Factory could handle a higher load. I have heard that it can get overloaded, and it can't handle it."
"I would like to see this time travel feature in Snowflake added to Azure Data Factory."
"Integration of data lineage would be a nice feature in terms of DevOps integration. It would make implementation for a company much easier. I'm not sure if that's already available or not. However, that would be a great feature to add if it isn't already there."
"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."
"Licensing costs for this Oracle solution are expensive. ODI forms an integral part of the overall PaaS solution and becomes a kind of backbone for that particular service, which is painful because from a PaaS perspective, the licensing costs just shoot off the roof."
"The solution is expensive."
"It's lacking a lot of mapping features that Oracle OSB and SOA have. It needs to evolve a lot."
"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."
"This is an expensive solution compared to other products on the market."
"I've found technical support not very effective. They should work to improve their services."
"The solution could be improved when it comes to bulk uploading; there are problems with it when you hit the upper limit."
 

Pricing and Cost Advice

"Understanding the pricing model for Data Factory is quite complex."
"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."
"ADF is cheaper compared to AWS."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"The licensing cost is included in the Synapse."
"The price is fair."
"The price you pay is determined by how much you use it."
"The price is competitive compared to Boomi which is much higher."
report
Use our free recommendation engine to learn which Data Integration solutions are best for your needs.
912,069 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
11%
Manufacturing Company
9%
Computer Software Company
8%
Construction Company
7%
Outsourcing Company
24%
Construction Company
14%
Comms Service Provider
10%
Financial Services Firm
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise64
By reviewers
Company SizeCount
Small Business3
Large Enterprise4
 

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...
Ask a question
Earn 20 points
 

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 Informatica, Palantir, Microsoft and others in Data Integration. Updated: August 2026.
912,069 professionals have used our research since 2012.