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Azure Data Factory vs TIBCO Live Datamart 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
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
91
Ranking in other categories
Data Integration (1st), Cloud Data Warehouse (2nd)
TIBCO Live Datamart
Average Rating
9.0
Reviews Sentiment
7.0
Number of Reviews
2
Ranking in other categories
Data Warehouse (23rd)
 

Featured Reviews

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.
Mohsin Pathan - PeerSpot reviewer
Standout features are real-time dashboards and powerful aggregation
This product has a powerful aggregating feature which is great. It also has its own APIs. Whenever the data comes in, it can be streamed out anywhere. It's the only solution that provides real-time dashboards. Tableau doesn't have this feature. The three variants of historical data, real-time data and predicted data from Spitfire, give more strength to LiveDatamart without any dependency on other products. The product is easy to set up with very low maintenance required.

Quotes from Members

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

Pros

"This solution will allow the organisation to improve its existing data offerings over time by adding predictive analytics, data sharing via APIs and other enhancements readily."
"It is easy to deploy workflows and schedule jobs."
"The data mapping and the ability to systematically derive data are nice features. It worked really well for the solution we had. It is visual, and it did the transformation as we wanted."
"The solution can scale very easily."
"The flexibility that Azure Data Factory offers is great."
"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."
"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."
"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 solution has a powerful aggregating feature"
"You can create your own rules that include mathematic calculations."
 

Cons

"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"Data Factory's performance during heavy data processing isn't great."
"The solution should offer better integration with Azure machine learning. We should be able to embed the cognitive services from Microsoft, for example as a web API. It should allow us to embed Azure machine learning in a more user-friendly way."
"The number of standard adaptors could be extended further."
"The initial setup is not very straightforward."
"I have not found any real shortcomings within the product."
"There is no built-in pipeline exit activity when encountering an error."
"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."
"The solution's setup could be quicker and easier."
"Improvements need to be made on the load balancing side."
 

Pricing and Cost Advice

"The pricing model is based on usage and is not cheap."
"The pricing is a bit on the higher end."
"Pricing is comparable, it's somewhere in the middle."
"Azure Data Factory gives better value for the price than other solutions such as Informatica."
"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 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."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"Data Factory is affordable."
"The solution might be considered a bit expensive because it competes with open-source products."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Government
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
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...
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Also Known As

No data available
Streambase, TIBCO LiveView Data Mart
 

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
Aerospace Corporation, Balfour Beatty Infrastructure Services, Banco Sabadell, Bolton Borough Council
Find out what your peers are saying about Azure Data Factory vs. TIBCO Live Datamart and other solutions. Updated: July 2025.
865,384 professionals have used our research since 2012.