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Azure Data Factory vs Rivery 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

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)
Rivery
Ranking in Data Integration
34th
Average Rating
8.6
Reviews Sentiment
7.3
Number of Reviews
2
Ranking in other categories
Migration Tools (4th), Cloud Migration (14th), Cloud Data Integration (19th)
 

Mindshare comparison

As of February 2025, in the Data Integration category, the mindshare of Azure Data Factory is 10.1%, down from 12.9% compared to the previous year. The mindshare of Rivery is 0.3%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

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.
reviewer2335923 - PeerSpot reviewer
Provides users with an initial setup phase, which is fairly simple to manage
I don't know what could be improved in terms of what my company was used to previously or after moving over to Rivery. I have not had much experience with platforms other than Rivery. For me, Rivalry was a way to step up from what we used. To be honest, I am not really sure what improvements could be made in Rivery. Pricing is a little steep for smaller organizations, I would say. The product's pricing model could be a little bit better. I am not aware if there are additional packages for smaller organizations, but if there are no packages available, then maybe that would be a good way to introduce something new in the tool.

Quotes from Members

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

Pros

"It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory."
"The valuable feature of Azure Data Factory is its integration capability, as it goes well with other components of Microsoft Azure."
"Azure Data Factory is a low code, no code platform, which is helpful."
"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."
"Most of our customers are Microsoft shops and prefer Azure Data Factory because they have good licensing options and a trust factor with Microsoft."
"Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process."
"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."
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."
"Connects to many APIs in the market and new ones are being added all the time."
"The solution's most valuable features are that it is quick to connect and simple to use."
 

Cons

"Azure Data Factory's pricing in terms of utilization could be improved."
"Snowflake connectivity was recently added and if the vendor provided some videos on how to create data then that would be helpful."
"They require more detailed error reporting, data normalization tools, easier connectivity to other services, more data services, and greater compatibility with other commonly used schemas."
"The one element of the solution that we have used and could be improved is the user interface."
"The pricing scheme is very complex and difficult to understand."
"I would like to see this time travel feature in Snowflake added to Azure Data Factory."
"The deployment should be easier."
"I would like to be informed about the changes ahead of time, so we are aware of what's coming."
"Lineage and an impact analysis or logic dependency are lacking."
"Pricing is a little steep for smaller organizations, I would say. The product's pricing model could be a little bit better."
 

Pricing and Cost Advice

"I don't see a cost; it appears to be included in general support."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"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."
"The price is fair."
"I would rate Data Factory's pricing nine out of ten."
"The price you pay is determined by how much you use it."
"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."
"Product is priced at the market standard."
"I rate the tool's price as six out of ten if I consider the lowest price to be one and the highest price to be ten."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
7%
Financial Services Firm
16%
Computer Software Company
11%
Manufacturing Company
10%
Government
10%
 

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...
What is your experience regarding pricing and costs for Rivery?
The tool's price can be a little steep for a small organization. I rate the tool's price as six out of ten if I consider the lowest price to be one and the highest price to be ten.
What needs improvement with Rivery?
I don't know what could be improved in terms of what my company was used to previously or after moving over to Rivery. I have not had much experience with platforms other than Rivery. For me, Rival...
What is your primary use case for Rivery?
My company has started to use the Rivery extract data from Hive. It is like a project management sort of program, and we started to use Rivery to get the data from there over into Mavenlink, so we ...
 

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. Rivery and other solutions. Updated: January 2025.
838,713 professionals have used our research since 2012.