Azure Data Factory vs Rivery comparison

Microsoft and Rivery are both solutions in the Data Integration category. Microsoft is ranked #3 with an average rating of 8.2, while Rivery is ranked #35 with an average rating of 8.0. Microsoft holds a 3.2% mindshare in DI, compared to Rivery’s 0.6% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of Rivery users who would recommend it.

Azure Data Factory

Read 93 Azure Data Factory reviews

11,197 Views
7,838 Comparison Views

92% willing to recommend

Rivery

Read 4 Rivery reviews

1,027 Views
698 Comparison Views

100% willing to recommend

Azure Data Factory

Rivery

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

Azure Data Factory and Rivery compete in the data integration space, each offering distinct advantages. Azure Data Factory is advantageous for those leveraging Microsoft Azure services heavily, while Rivery focuses on automation and scalability, appealing to businesses managing large data volumes.

Features: Azure Data Factory provides native integration with Azure services, advanced data orchestration, and comprehensive data transformation options. Rivery offers automated data pipelines, outstanding scalability, and easy adaptation to dynamic environments, catering to complex data workflows.

Ease of Deployment and Customer Service: Azure Data Factory may present deployment challenges but benefits from robust support within the Microsoft ecosystem. Rivery features a straightforward, no-code deployment, making it accessible to organizations with limited technical expertise. Both offer extensive customer support, though Rivery's simplified approach can appeal to teams with fewer resources.

Pricing and ROI: Azure Data Factory's flexible pricing aligns with Microsoft's other services, creating potential cost efficiencies for users within the ecosystem. Rivery's pricing structure is more transparent and can seem higher; however, the potential for significant ROI from its advanced capabilities is attractive for data-centric operations.

To learn more, read our detailed Azure Data Factory vs. Rivery Report (Updated: December 2025).

Buyer's Guide

Azure Data Factory vs. Rivery

December 2025

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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

Ranking in other categories

Cloud Data Warehouse (2nd)

Rivery

Ranking in Data Integration

35th

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Migration Tools (3rd), Cloud Migration (15th), Cloud Data Integration (19th)

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 Rivery is 0.6%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Market Share Distribution
Product	Market Share (%)
Azure Data Factory	3.2%
Rivery	0.6%
Other	96.2%

Data Integration

Featured Reviews

KandaswamyMuthukrishnan

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.

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Doron Matmoni

Manager, Application at a non-profit with 1,001-5,000 employees

Data pipelines have become streamlined and now connect diverse sources with strong support

How Rivery can be improved is a challenging question, but I think something with the graphics could be better because when there is a lot of code inside, it needs to be more user-friendly. I am not talking about the source-to-target, but when we implement a lot of code, you need a different visual of how you use it, such as what you see in DBT. There is a problem where sometimes I run a river and something in the UI does not get refreshed because I think of browser cache limits, which is annoying. I always need to refresh, and then I am not sure, so I have to go inside the river and look in the log to see if it has finished or not, which takes my time. At the end of the day, when I am running the river, I need it to be done before I go to the next step. Something in the UI could work more smoothly to show it easily. I am not sure why it happens, and I am not sure if there is a solution for it, but if it could be more clear, that would be very nice, such as sending an email once the river is really done.

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Quotes from Members

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

Pros

"ADF is another ETL tool similar to Informatica that can transform data or copy it from on-prem to the cloud or vice versa. Once we have the data, we can apply various transformations to it and schedule our pipeline according to our business needs. ADF integrates with Databricks. We can call our Databricks notebooks and schedule them via ADF."

"The best part of this product is the extraction, transformation, and load."

"The scalability of the product is impressive."

"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."

"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."

"Powerful but easy-to-use and intuitive."

"Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."

"Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness."

More Azure Data Factory pros

"Connects to many APIs in the market and new ones are being added all the time."

"Rivery has positively impacted my organization by enabling us to create a stable pipeline, and we can expand the variety of the data sources as we go very easily, with no worries, and with a lot of confidence in the fact that it can be done."

"Rivery has positively impacted my organization by helping me streamline my data ingestion and transformation processes, especially in combination with Snowflake."

"The solution's most valuable features are that it is quick to connect and simple to use."

Cons

"I have encountered a problem with the integration with third-party solutions, particularly with SAP."

"The initial setup is not very straightforward."

"I would like to see this time travel feature in Snowflake added to Azure Data Factory."

"Azure Data Factory uses many resources and has issues with parallel workflows."

"There's space for improvement in the development process of the data pipelines."

"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."

"There is no built-in pipeline exit activity when encountering an error."

"Lacks in-built streaming data processing."

More Azure Data Factory cons

"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."

"My experience with pricing, setup cost, and licensing was unfortunately not so good in my recent data project."

Pricing and Cost Advice

"Data Factory is expensive."

"The price you pay is determined by how much you use it."

"The licensing cost is included in the Synapse."

"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."

"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."

"ADF is cheaper compared to AWS."

"This is a cost-effective solution."

More Azure Data Factory pricing and cost advice

"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

11%

Manufacturing Company

Government

Manufacturing Company

11%

Comms Service Provider

10%

Computer Software Company

10%

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	19
Large Enterprise	57

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.

See all answers

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...

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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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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.

See all answers

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...

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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 ...

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Comparisons

Snowflake vs Azure Data Factory

Compared 7% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Azure Data Factory

Compared 6% of the time

Palantir Foundry vs Azure Data Factory

Compared 5% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 4% of the time

FME vs Azure Data Factory

Compared 4% of the time

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Compared 17% of the time

Matillion Data Productivity Cloud vs Rivery

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OpenText Migrate vs Rivery

Compared 9% of the time

AWS Glue vs Rivery

Compared 8% of the time

Fivetran vs Rivery

Compared 7% of the time

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Product Reports

Buyer's Guide

Azure Data Factory

January 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

January 2026

Download Rivery product report

Overview

Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.

Microsoft

Rivery is a serverless, SaaS DataOps platform that empowers companies of all sizes around the world to consolidate, orchestrate, and manage internal and external data sources with ease and efficiency.

By offering comprehensive data solutions and partnering with complementary technology providers, including Google, Snowflake, Tableau, and Looker, Rivery enables data-driven companies to build the perfect ecosystems for all their data processes.

Rivery

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

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Buyer's Guide

Azure Data Factory vs. Rivery

December 2025

Free Report: Azure Data Factory vs. Rivery

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