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Ab Initio Co>Operating System vs Azure Data Factory comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 2024

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

Ab Initio Co>Operating System
Ranking in Data Integration
27th
Average Rating
8.8
Reviews Sentiment
6.8
Number of Reviews
5
Ranking in other categories
Workload Automation (18th)
Azure Data Factory
Ranking in Data Integration
3rd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
94
Ranking in other categories
Cloud Data Warehouse (2nd)
 

Mindshare comparison

As of March 2026, in the Data Integration category, the mindshare of Ab Initio Co>Operating System is 1.2%, down from 1.4% compared to the previous year. The mindshare of Azure Data Factory is 2.8%, down from 9.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.8%
Ab Initio Co>Operating System1.2%
Other96.0%
Data Integration
 

Featured Reviews

AM
Senior Solutions Architect at IDS Comercial
Enables creation of sophisticated applications with powerful parallelism and quick, effective support
The most valuable features of Ab Initio Co>Operating System are its performance and the ability to implement parallelism. There are three kinds of parallelism in Ab Initio Co>Operating System, which allow us to create very sophisticated solutions for almost any kind of application. This parallelism is one of the strongest features. Additionally, its scalability offers a unique way to escalate applications that differs from other technologies. In terms of data processing, the emphasis is on understanding the data. Data profiling is fundamental, and Ab Initio Co>Operating System integrates tools to perform this within the GDE, as well as specialized products for this purpose. Data profiling graphs can be implemented when necessary to understand the data sources.
KandaswamyMuthukrishnan - PeerSpot reviewer
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.

Quotes from Members

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

Pros

"Ab Initio reaches the highest performance and is very flexible in processing huge amounts of data."
"Ab Initio Co>Operating System support is the best I have encountered."
"Ab Initio Co>Operating System excels at providing data lineage regardless of the type of data I have."
"The graphical interface of Ab Initio Co>Operating System is very easy to understand and allows me to visualize the data flow effectively."
"Co>Operating System's most valuable feature is its ability to process bulk data effectively."
"It is easy to deploy workflows and schedule jobs."
"Data Factory allows you to pull data from multiple systems, transform it according to your business needs, and load it into a data warehouse or data lake."
"Azure Data Factory is a low code, no code platform, which is helpful."
"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."
"It's extremely consistent."
"I enjoy the ease of use for the backend JSON generator, the deployment solution, and the template management."
"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."
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."
 

Cons

"An awesome improvement would be big data solutions, for example, implementing some kind of business intelligence or neural networks for artificial intelligence."
"While Ab Initio Co>Operating System has positive attributes, I find that certain features can sometimes be difficult to understand."
"Ab Initio Co>Operating System is a very expensive product."
"Co>Operating System would be improved with more integrations for less well-known technologies."
"There aren't many third-party extensions or plugins available in the solution."
"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."
"The product integration with advanced coding options could cater to users needing more customization."
"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."
"I would like to see this time travel feature in Snowflake added to Azure Data Factory."
"There is no built-in pipeline exit activity when encountering an error."
"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."
"The solution needs to be more connectable to its own services."
 

Pricing and Cost Advice

"Co>Operating System's pricing is on the expensive end since it tends to be used by big enterprises."
"The solution is cheap."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"Azure Data Factory gives better value for the price than other solutions such as Informatica."
"The licensing is a pay-as-you-go model, where you pay for what you consume."
"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."
"Data Factory is affordable."
"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."
"Understanding the pricing model for Data Factory is quite complex."
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Top Industries

By visitors reading reviews
Financial Services Firm
28%
Computer Software Company
7%
Healthcare Company
6%
Comms Service Provider
6%
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
9%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise20
Large Enterprise57
 

Questions from the Community

What needs improvement with Ab Initio Co>Operating System?
While Ab Initio Co>Operating System has positive attributes, I find that certain features can sometimes be difficult to understand. When I have too many import feeds opened, they can conflict wi...
What is your primary use case for Ab Initio Co>Operating System?
The flexibility of data type and source integration for my IT ecosystem is excellent because Ab Initio Co>Operating System uses metadata, so it doesn't actually access the data; it takes the dat...
What advice do you have for others considering Ab Initio Co>Operating System?
I have not been involved in the security access of the platform's data security features, but I know that Ab Initio Co>Operating System is very careful because it doesn't access any customer dat...
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...
 

Also Known As

Co>Operating System
No data available
 

Overview

 

Sample Customers

A multinational transportation company
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
Find out what your peers are saying about Ab Initio Co>Operating System vs. Azure Data Factory and other solutions. Updated: March 2026.
884,873 professionals have used our research since 2012.