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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
24th
Average Rating
8.8
Reviews Sentiment
6.8
Number of Reviews
5
Ranking in other categories
Workload Automation (19th)
Azure Data Factory
Ranking in Data Integration
3rd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
93
Ranking in other categories
Cloud Data Warehouse (2nd)
 

Mindshare comparison

As of January 2026, in the Data Integration category, the mindshare of Ab Initio Co>Operating System is 1.3%, up from 1.3% compared to the previous year. The mindshare of Azure Data Factory is 3.2%, down from 10.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Azure Data Factory3.2%
Ab Initio Co>Operating System1.3%
Other95.5%
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

"The graphical interface of Ab Initio Co>Operating System is very easy to understand and allows me to visualize the data flow effectively."
"Ab Initio Co>Operating System excels at providing data lineage regardless of the type of data I have."
"Co>Operating System's most valuable feature is its ability to process bulk data effectively."
"Ab Initio Co>Operating System support is the best I have encountered."
"Ab Initio reaches the highest performance and is very flexible in processing huge amounts of data."
"The most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."
"I think it makes it very easy to understand what data flow is and so on. You can leverage the user interface to do the different data flows, and it's great. I like it a lot."
"The most valuable feature is the ease in which you can create an ETL pipeline."
"Data Factory's best features are simplicity and flexibility."
"We use the solution to move data from on-premises to the cloud."
"It is easy to integrate."
"I find that the solution integrates well with cloud technologies, which we are using for different clouds like Snowflake and AWS"
"The function of the solution is great."
 

Cons

"An awesome improvement would be big data solutions, for example, implementing some kind of business intelligence or neural networks for artificial intelligence."
"Ab Initio Co>Operating System is a very expensive product."
"While Ab Initio Co>Operating System has positive attributes, I find that certain features can sometimes be difficult to understand."
"Co>Operating System would be improved with more integrations for less well-known technologies."
"I have not found any real shortcomings within the product."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"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."
"Customer service is not satisfactory. Third-party personnel handle support and rely on a knowledge repository."
"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."
"Azure Data Factory can improve by having support in the drivers for change data capture."
"The solution needs to be more connectable to its own services."
"There is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration."
 

Pricing and Cost Advice

"Co>Operating System's pricing is on the expensive end since it tends to be used by big enterprises."
"Data Factory is expensive."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"The pricing model is based on usage and is not cheap."
"Data Factory is affordable."
"The price is fair."
"The solution's pricing is competitive."
"The pricing is a bit on the higher end."
"I would not say that this product is overly expensive."
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Top Industries

By visitors reading reviews
Financial Services Firm
31%
Computer Software Company
9%
Insurance Company
5%
Healthcare Company
5%
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Government
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
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: December 2025.
879,768 professionals have used our research since 2012.