CloverETL vs Spring Cloud Data Flow comparison

Javlin and VMware are both solutions in the Data Integration category. Javlin is ranked #65, while VMware is ranked #24 with an average rating of 7.7. Javlin holds a 0.2% mindshare in DI, compared to VMware’s 1.1% mindshare. Additionally, 100% of Javlin users are willing to recommend the solution, compared to 88% of VMware users who would recommend it.

CloverETL

Read 2 CloverETL reviews

200 Views
159 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

CloverETL

Spring Cloud Data Flow

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Executive SummaryUpdated on Dec 19, 2024

CloverETL and Spring Cloud Data Flow are competing products in the data integration and stream processing market. Spring Cloud Data Flow holds an advantage due to its robust feature set, aligning well with modern cloud-based use cases.

Features: CloverETL provides comprehensive ETL capabilities, strong data transformation features, and a designed approach for batch processing. Spring Cloud Data Flow supports microservices architecture, can handle real-time streaming data, and is ideal for cloud-native applications.

Ease of Deployment and Customer Service:CloverETL offers an easy deployment model and reliable customer service, making it accessible for organizations with limited resources. Spring Cloud Data Flow is tailored for modern cloud environments, may have deployment complexities, but is well-supported by the Spring ecosystem and community.

Pricing and ROI: CloverETL has a straightforward pricing structure, providing steady ROI through dependable data processing. Spring Cloud Data Flow offers flexible pricing, potentially yielding significant ROI via scalable data processing, despite possible higher initial setup costs.

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

Buyer's Guide

CloverETL 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

CloverETL

Ranking in Data Integration

65th

Average Rating

7.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Visualization (47th)

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 April 2025, in the Data Integration category, the mindshare of CloverETL is 0.2%, 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

it_user854766

Vice President, Information and Technology Services at a tech services company with 11-50 employees

Provides wealth of pre-defined, customizable components, and descriptive logging for errors

* Familiar, intuitive GUI (Eclipse plug-in) coming from a Java development background. * In-depth, descriptive, and well-laid-out documentation. * Responsive support through forums, even directly from Clover staff. * Wealth of pre-defined components. * All components are customizable. * Descriptive logging, especially for error messages. * Ease of install/light footprint.

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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

"Server features for scheduler: It is very easy to schedule jobs and monitor them. The interface is easy to use."

"Key features include wealth of pre-defined components; all components are customizable; descriptive logging, especially for error messages."

"No dependence on native language and ease of use."

"Connectivity to various data sources: The ability to extract data from different data sources gives greater flexibility."

"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 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."

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

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

"The product is very user-friendly."

"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 most valuable feature is real-time streaming."

Cons

"Its documentation could be improved."

"Resource management: We typically run out of heap space, and even the allocation of high heap space does not seem to be enough."

"Needs: easier automated failure recovery; more, and more intuitive auto-generated/filled-in code for components; easier/more automated sync between CloverETL Designer and CloverETL Server."

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

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

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

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

"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."

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

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

"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."

Pricing and Cost Advice

Information not available

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

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

"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

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Financial Services Firm

26%

Computer Software Company

17%

Retailer

Manufacturing Company

Company Size

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Large Enterprise

Midsize Enterprise

Small Business

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Questions from the Community

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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...

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Comparisons

No data available

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Compared 11% of the time

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Compared 7% of the time

Apache Spark Streaming vs Spring Cloud Data Flow

Compared 5% of the time

MuleSoft Anypoint Platform vs Spring Cloud Data Flow

Compared 4% of the time

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Product Reports

Buyer's Guide

Data Integration

March 2025

Download CloverETL product report

Buyer's Guide

Spring Cloud Data Flow

March 2025

Download Spring Cloud Data Flow product report

Overview

CloverETL is a rapid, end-to-end data integration solution. Businesses choose CloverETL for its usability and intuitive controls, along with its lightweight footprint, flexibility, and processing speed. Achieving true, rapid data integration means much more than just raw data processing power. Rapid refers to an end-to-end process that begins the moment a data-related problem is recognized to the point when the data is in the right place and form to be analyzed and monetized.

Javlin

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

Sample Customers

IBM, Oracle, MuleSoft, GoodData, Thomson Reuters, salesforce.com, Comcast, Active Network, SHOP.CA

Information Not Available

Buyer's Guide

CloverETL vs. Spring Cloud Data Flow

April 2025

Free Report: CloverETL vs. Spring Cloud Data Flow

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