Try our new research platform with insights from 80,000+ expert users

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
47th
Average Rating
9.4
Reviews Sentiment
7.9
Number of Reviews
3
Ranking in other categories
Workload Automation (29th)
Azure Data Factory
Ranking in Data Integration
1st
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
90
Ranking in other categories
Cloud Data Warehouse (3rd)
 

Mindshare comparison

As of April 2025, in the Data Integration category, the mindshare of Ab Initio Co>Operating System is 1.5%, up from 0.6% compared to the previous year. The mindshare of Azure Data Factory is 9.5%, down from 12.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

AM
High performance and flexible solution for companies with large amounts of data
My primary use of this solution is in the banking sector to process financial movements and generate reports. I also use it in the risk area of banking to detect thefts and risky behaviors Ab Initio reaches the highest performance and is very flexible in processing huge amounts of data.  An…
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.

Quotes from Members

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

Pros

"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."
"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."
"For developers that are very accustomed to the Microsoft development studio, it's very easy for them to complete end-to-end data integration."
"One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect."
"The initial setup is very quick and easy."
"In terms of my personal experience, it works fine."
"From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connects and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature."
"Azure Data Factory became more user-friendly when data-flows were introduced."
"The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem."
 

Cons

"Co>Operating System would be improved with more integrations for less well-known technologies."
"An awesome improvement would be big data solutions, for example, implementing some kind of business intelligence or neural networks for artificial intelligence."
"I rate Azure Data Factory six out of 10 for stability. ADF is stable now, but we had problems recently with indexing on an SQL database. It's slow when dealing with a huge volume of data. It depends on whether the database is configured as general purpose or hyperscale."
"Data Factory's cost is too high."
"There aren't many third-party extensions or plugins available in the solution."
"Azure Data Factory uses many resources and has issues with parallel workflows."
"Snowflake connectivity was recently added and if the vendor provided some videos on how to create data then that would be helpful."
"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."
"Data Factory could be improved in terms of data transformations by adding more metadata extractions."
"The user interface could use improvement. It's not a major issue but it's something that can be improved."
 

Pricing and Cost Advice

"Co>Operating System's pricing is on the expensive end since it tends to be used by big enterprises."
"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."
"I would not say that this product is overly expensive."
"The solution's pricing is competitive."
"Pricing appears to be reasonable in my opinion."
"Product is priced at the market standard."
"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."
"Azure Data Factory gives better value for the price than other solutions such as Informatica."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
report
Use our free recommendation engine to learn which Data Integration solutions are best for your needs.
845,406 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
38%
Computer Software Company
9%
Insurance Company
7%
University
5%
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

Ask a question
Earn 20 points
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 2025.
845,406 professionals have used our research since 2012.