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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
93
Ranking in other categories
Cloud Data Warehouse (2nd)
 

Mindshare comparison

As of February 2026, in the Data Integration category, the mindshare of Ab Initio Co>Operating System is 1.2%, down from 1.3% compared to the previous year. The mindshare of Azure Data Factory is 3.0%, down from 9.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Azure Data Factory3.0%
Ab Initio Co>Operating System1.2%
Other95.8%
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."
"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."
"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 overall performance is quite good."
"The scalability of the product is impressive."
"The data copy template is a valuable feature."
"The tool's most valuable features are its connectors. It has many out-of-the-box connectors. We use ADF for ETL processes. Our main use case involves integrating data from various databases, processing it, and loading it into the target database. ADF plays a crucial role in orchestrating these ETL workflows."
"An excellent tool for pipeline orchestration."
"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."
"One advantage of Azure Data Factory is that it's fast, unlike SSIS and other on-premise tools. It's also very convenient because it has multiple connectors. The availability of native connectors allows you to connect to several resources to analyze data streams."
"The best part of this product is the extraction, transformation, and load."
 

Cons

"While Ab Initio Co>Operating System has positive attributes, I find that certain features can sometimes be difficult to understand."
"An awesome improvement would be big data solutions, for example, implementing some kind of business intelligence or neural networks for artificial intelligence."
"Co>Operating System would be improved with more integrations for less well-known technologies."
"Ab Initio Co>Operating System is a very expensive product."
"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"The thing we missed most was data update, but this is now available as of two weeks ago."
"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."
"When we initiated the cluster, it took some time to start the process."
"Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically."
"Data Factory could be improved by eliminating the need for a physical data area. We have to extract data using Data Factory, then create a staging database for it with Azure SQL, which is very, very expensive. Another improvement would be lowering the licensing cost."
"There is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration."
"Lacks in-built streaming data processing."
 

Pricing and Cost Advice

"Co>Operating System's pricing is on the expensive end since it tends to be used by big enterprises."
"This is a cost-effective solution."
"Data Factory is expensive."
"The pricing model is based on usage and is not cheap."
"The solution's pricing is competitive."
"Azure products generally offer competitive pricing, suitable for diverse budget considerations."
"The price is fair."
"I would rate Data Factory's pricing nine out of ten."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
31%
Computer Software Company
7%
Healthcare Company
5%
Insurance Company
5%
Financial Services Firm
13%
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 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: February 2026.
881,733 professionals have used our research since 2012.