Azure Data Factory vs Rivery comparison

Microsoft and Rivery are both solutions in the Data Integration category. Microsoft is ranked #1 with an average rating of 8.1, while Rivery is ranked #36 with an average rating of 8.0. Microsoft holds a 11.0% mindshare in DI, compared to Rivery’s 0.2% 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 86 Azure Data Factory reviews

21,615 Views
17,232 Comparison Views

92% willing to recommend

Rivery

Read 2 Rivery reviews

272 Views
195 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 2024).

Buyer's Guide

Azure Data Factory vs. Rivery

December 2024

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Categories and Ranking

Azure Data Factory

Ranking in Data Integration

1st

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (3rd)

Rivery

Ranking in Data Integration

36th

Average Rating

8.6

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

Migration Tools (4th), Cloud Migration (16th), Cloud Data Integration (21st)

Mindshare comparison

As of December 2024, in the Data Integration category, the mindshare of Azure Data Factory is 11.0%, down from 13.3% compared to the previous year. The mindshare of Rivery is 0.2%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

Thulani David Mngadi

Data architect at Old Mutual

Data flow feature is valuable for data transformation tasks

The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem.

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reviewer2335923

Senior Operations Analyst at a computer software company with 201-500 employees

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.

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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

"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."

"The solution can scale very easily."

"Its integrability with the rest of the activities on Azure is most valuable."

"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."

"The security of the agent that is installed on-premises is very good."

"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."

"On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good."

"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."

More Azure Data Factory pros

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

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

Cons

"When we initiated the cluster, it took some time to start the process."

"The product's technical support has certain shortcomings, making it an area where improvements are required."

"Azure Data Factory can improve by having support in the drivers for change data capture."

"There are limitations when processing more than one GD file."

"Data Factory's cost is too high."

"I would like to be informed about the changes ahead of time, so we are aware of what's coming."

"Data Factory's monitorability could be better."

"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."

More Azure Data Factory cons

"Pricing is a little steep for smaller organizations, I would say. The product's pricing model could be a little bit better."

"Lineage and an impact analysis or logic dependency are lacking."

Pricing and Cost Advice

"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."

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."

"Data Factory is expensive."

"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."

"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."

"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

12%

Manufacturing Company

Healthcare Company

Financial Services Firm

16%

Computer Software Company

12%

Government

12%

Manufacturing Company

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.

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?

See all answers

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

Informatica PowerCenter vs Azure Data Factory

Compared 13% of the time

Snowflake vs Azure Data Factory

Compared 10% of the time

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

Compared 8% of the time

Alteryx Designer vs Azure Data Factory

Compared 7% of the time

IBM InfoSphere DataStage vs Azure Data Factory

Compared 4% of the time

More Azure Data Factory Competitors

dbt vs Rivery

Compared 41% of the time

Alteryx Designer vs Rivery

Compared 32% of the time

More Rivery Competitors

Product Reports

Buyer's Guide

Azure Data Factory

December 2024

Download Azure Data Factory product report

Buyer's Guide

Data Integration

December 2024

Download Rivery product report

Learn More

Microsoft

Rivery

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.

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.

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 2024

Free Report: Azure Data Factory vs. Rivery

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