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Azure Data Factory vs TetraScience comparison

 

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
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)
TetraScience
Ranking in Data Integration
56th
Average Rating
6.6
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of March 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.8%, down from 9.7% compared to the previous year. The mindshare of TetraScience is 0.3%. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.8%
TetraScience0.3%
Other96.9%
Data Integration
 

Featured Reviews

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.
Varun Khandavalli - PeerSpot reviewer
Senior Specialist Engineering Dev. & Integration at a manufacturing company with 10,001+ employees
Efficient data integration and good automation with challenging configurability
The application has a difficult-to-use parsing capability, which requires a lot of reengineering when the use case isn't specifically met. The application also lacks capabilities within its terminal commands that are not available in their GUI. It requires a lot of configurability, which could be streamlined for an enterprise application user.

Quotes from Members

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

Pros

"I am one hundred percent happy with the stability."
"Azure Data Factory is great because it's a cloud service; you do not have to take care of the installation and configuration yourself."
"The initial setup is pretty simple and it can be deployed in a couple of hours."
"Synapse was the better choice for us to implement, as it has a lot of out-of-the-box connectors that we can utilize for data transformation and organization."
"If you have Azure as a cloud service and you want to perform ETL then Azure Data Factory is a product that I can recommend."
"The solution has a good interface and the integration with GitHub is very useful."
"The feature I found most helpful in Azure Data Factory is the pipeline feature, including being able to connect to different sources. Azure Data Factory also has built-in security, which is another valuable feature."
"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."
"The ingestion engines were pretty good."
"The crawler agents they provide, as well as TetraScience exclusive parsers, allow for specific instruments that we use in our labs with proprietary formats to extract data and put it into more standard formats for various purposes."
 

Cons

"I did not see any positive impact from Azure Data Factory overall."
"I have encountered a problem with the integration with third-party solutions, particularly with SAP."
"If the user interface was more user friendly and there was better error feedback, it would be helpful."
"There's no Oracle connector if you want to do transformation using data flow activity, so Azure Data Factory needs more connectors for data flow transformation."
"We have experienced some issues with the integration. This is an area that needs improvement."
"The user interface could use improvement. It's not a major issue but it's something that can be improved."
"Compared to Informatica, it's really crude. I think it's a very crude solution."
"The solution needs to integrate more with other providers and should have a closer integration with Oracle BI."
"While functional during ingestion workflows, the automation toolkit required manual processes."
"The application has a difficult-to-use parsing capability, which requires a lot of reengineering when the use case isn't specifically met."
 

Pricing and Cost Advice

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"The solution's pricing is competitive."
"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."
"The pricing is a bit on the higher end."
"This is a cost-effective solution."
"My company is on a monthly subscription for Azure Data Factory, but it's more of a pay-as-you-go model where your monthly invoice depends on how many resources you use. On a scale of one to five, pricing for Azure Data Factory is a four. It's just the usage fees my company pays monthly."
"Pricing is comparable, it's somewhere in the middle."
"It's not particularly expensive."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
10%
Manufacturing Company
9%
Government
6%
Construction Company
34%
Computer Software Company
12%
Pharma/Biotech Company
9%
Manufacturing Company
6%
 

Company Size

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

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...
What needs improvement with TetraScience?
The application has a difficult-to-use parsing capability, which requires a lot of reengineering when the use case isn't specifically met. The application also lacks capabilities within its termina...
What is your primary use case for TetraScience?
TetraScience is a platform that integrates instruments into a laboratory environment into other software applications that can help leverage the data. In most pharma companies, the application is u...
What advice do you have for others considering TetraScience?
I would approach with caution. The platform has a high knowledge gap and the proprietary nature of its parsers and crawling agents. Before approaching TetraScience, have your use case in hand and u...
 

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
Information Not Available
Find out what your peers are saying about Azure Data Factory vs. TetraScience and other solutions. Updated: March 2026.
885,311 professionals have used our research since 2012.