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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
93
Ranking in other categories
Cloud Data Warehouse (2nd)
TetraScience
Ranking in Data Integration
52nd
Average Rating
6.6
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of January 2026, in the Data Integration category, the mindshare of Azure Data Factory is 3.2%, down from 10.0% compared to the previous year. The mindshare of TetraScience is 0.2%. It is calculated based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Azure Data Factory3.2%
TetraScience0.2%
Other96.6%
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

"The most valuable feature is the ease in which you can create an ETL pipeline."
"The solution can scale very easily."
"The data flows were beneficial, allowing us to perform multiple transformations."
"Powerful but easy-to-use and intuitive."
"It makes it easy to collect data from different sources."
"The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable."
"The flexibility that Azure Data Factory offers is great."
"In terms of my personal experience, it works fine."
"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

"The user interface could use improvement. It's not a major issue but it's something that can be improved."
"When we initiated the cluster, it took some time to start the process."
"The product could provide more ways to import and export data."
"Some of the optimization techniques are not scalable."
"There should be a way that it can do switches, so if at any point in time I want to do some hybrid mode of making any data collections or ingestions, I can just click on a button."
"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."
"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"The support and the documentation can be improved."
"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

"The pricing model is based on usage and is not cheap."
"The solution's pricing is competitive."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"The licensing cost is included in the Synapse."
"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."
"Azure Data Factory gives better value for the price than other solutions such as Informatica."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
11%
Manufacturing Company
9%
Government
7%
Computer Software Company
22%
Pharma/Biotech Company
17%
Manufacturing Company
8%
Government
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
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: December 2025.
881,114 professionals have used our research since 2012.