Rivery vs Spring Cloud Data Flow comparison

Rivery and VMware are both solutions in the Data Integration category. Rivery is ranked #34 with an average rating of 8.0, while VMware is ranked #24 with an average rating of 7.7. Rivery holds a 0.4% mindshare in DI, compared to VMware’s 1.1% mindshare. Additionally, 100% of Rivery users are willing to recommend the solution, compared to 88% of VMware users who would recommend it.

Rivery

Read 2 Rivery reviews

301 Views
217 Comparison Views

100% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

1,421 Views
1,057 Comparison Views

88% willing to recommend

Rivery

Spring Cloud Data Flow

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Executive SummaryUpdated on Dec 19, 2024

Spring Cloud Data Flow and Rivery compete in the data integration and workflow management space. Rivery has the upper hand due to its wide range of integrations, automation capabilities, and ease of deployment.

Features: Spring Cloud Data Flow offers seamless microservices orchestration, integration with Spring ecosystem tools, and customization flexibility. Rivery provides a no-code interface for rapid deployment, an extensive library of pre-built connectors, and competitive automation features.

Ease of Deployment and Customer Service: Spring Cloud Data Flow, being open-source, allows for in-depth customization but may require more setup time. Rivery offers an intuitive deployment model and responsive customer support, making it suitable for organizations with limited technical resources.

Pricing and ROI: Spring Cloud Data Flow has a lower initial setup cost due to its open-source nature, reducing long-term expenses for skilled teams. Rivery's pricing reflects its comprehensive features and ease of use, offering higher ROI for businesses prioritizing quick deployments and extensive data integration capabilities.

To learn more, read our detailed Rivery vs. Spring Cloud Data Flow Report (Updated: April 2025).

Buyer's Guide

Rivery vs. Spring Cloud Data Flow

April 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

Rivery

Ranking in Data Integration

34th

Average Rating

8.6

Reviews Sentiment

7.3

Number of Reviews

Ranking in other categories

Migration Tools (4th), Cloud Migration (13th), Cloud Data Integration (19th)

Spring Cloud Data Flow

Ranking in Data Integration

24th

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (9th)

Mindshare comparison

As of May 2025, in the Data Integration category, the mindshare of Rivery is 0.4%, up from 0.1% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.1%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

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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NitinGoyal

Engineering Lead at Naukri.com

Has a plug-and-play model and provides good robustness and scalability

The solution's community support could be improved. I don't know why the Spring Cloud Data Flow community is not very strong. Community support is very limited whenever you face any problem or are stuck somewhere. I'm not sure whether it has improved in the last six months because this pipeline was set up almost two years ago. I struggled with that a lot. For example, there was limited support whenever I got an exception and sought help from Stack Overflow or different forums. Interacting with Kubernetes needs a few certificates. You need to define all the certificates within your application. With the help of those certificates, your Java application or Spring Cloud Data Flow can interact with Kubernetes. I faced a lot of hurdles while placing those certificates. Despite following the official documentation to define all the replicas, readiness, and liveliness probes within the Spring Cloud Data Flow application, it was not working. So, I had to troubleshoot while digging in and debugging the internals of Spring Cloud Data Flow at that time. It was just a configuration mismatch, and I was doing nothing weird. There was a small spelling difference between how Spring Cloud Data Flow was expecting it and how I passed it. I was just following the official documentation.

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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

"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."

"The dashboards in Spring Cloud Dataflow are quite valuable."

"The best thing I like about Spring Cloud Data Flow is its plug-and-play model."

"The product is very user-friendly."

"There are a lot of options in Spring Cloud. It's flexible in terms of how we can use it. It's a full infrastructure."

"The most valuable feature is real-time streaming."

"The most valuable features of Spring Cloud Data Flow are the simple programming model, integration, dependency Injection, and ability to do any injection. Additionally, auto-configuration is another important feature because we don't have to configure the database and or set up the boilerplate in the database in every project. The composability is good, we can create small workloads and compose them in any way we like."

"The ease of deployment on Kubernetes, the seamless integration for orchestration of various pipelines, and the visual dashboard that simplifies operations even for non-specialists such as quality analysts."

"The solution's most valuable feature is that it allows us to use different batch data sources, retrieve the data, and then do the data processing, after which we can convert and store it in the target."

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."

"The solution's community support could be improved."

"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."

"Spring Cloud Data Flow could improve the user interface. We can drag and drop in the application for the configuration and settings, and deploy it right from the UI, without having to run a CI/CD pipeline. However, that does not work with Kubernetes, it only works when we are working with jars as the Spring Cloud Data Flow applications."

"Spring Cloud Data Flow is not an easy-to-use tool, so improvements are required."

"There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or refreshing the dashboard."

"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."

"Some of the features, like the monitoring tools, are not very mature and are still evolving."

"I would improve the dashboard features as they are not very user-friendly."

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."

"This is an open-source product that can be used free of charge."

"The solution provides value for money, and we are currently using its community edition."

"If you want support from Spring Cloud Data Flow there is a fee. The Spring Framework is open-source and this is a free solution."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Manufacturing Company

12%

Computer Software Company

12%

Government

11%

Financial Services Firm

26%

Computer Software Company

18%

Retailer

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

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.

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What needs improvement with Rivery?

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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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What needs improvement with Spring Cloud Data Flow?

There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or r...

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What is your primary use case for Spring Cloud Data Flow?

We had a project for content management, which involved multiple applications each handling content ingestion, transformation, enrichment, and storage for different customers independently. We want...

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What advice do you have for others considering Spring Cloud Data Flow?

I would definitely recommend Spring Cloud Data Flow. It requires minimal additional effort or time to understand how it works, and even non-specialists can use it effectively with its friendly docu...

See all answers

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Product Reports

Buyer's Guide

Data Integration

March 2025

Download Rivery product report

Buyer's Guide

Spring Cloud Data Flow

April 2025

Download Spring Cloud Data Flow product report

Overview

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

Spring Cloud Data Flow is a toolkit for building data integration and real-time data processing pipelines.
Pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. This makes Spring Cloud Data Flow suitable for a range of data processing use cases, from import/export to event streaming and predictive analytics. Use Spring Cloud Data Flow to connect your Enterprise to the Internet of Anything—mobile devices, sensors, wearables, automobiles, and more.

VMware

Buyer's Guide

Rivery vs. Spring Cloud Data Flow

April 2025

Free Report: Rivery vs. Spring Cloud Data Flow

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