Pentaho Data Integration and Analytics vs Spring Cloud Data Flow comparison

Hitachi Vantara and Broadcom are both solutions in the Data Integration category. Hitachi Vantara is ranked #8 with an average rating of 7.6, while Broadcom is ranked #22 with an average rating of 7.8. Hitachi Vantara holds a 1.6% mindshare in DI, compared to Broadcom’s 1.1% mindshare. Additionally, 95% of Hitachi Vantara users are willing to recommend the solution, compared to 88% of Broadcom users who would recommend it.

Pentaho Data Integration an...

Read 60 Pentaho Data Integration and Analytics reviews

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3,181 Comparison Views

95% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

3,140 Views
1,601 Comparison Views

88% willing to recommend

Pentaho Data Integration an...

Spring Cloud Data Flow

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Executive SummaryUpdated on Dec 19, 2024

Pentaho Data Integration and Analytics and Spring Cloud Data Flow are prominent in the data integration and microservices orchestration sector. Pentaho leads in data transformation and big data support, thanks to its robust compatibility and open-source community, while Spring Cloud's strength lies in cloud-native microservices orchestration and flexibility.

Features: Pentaho offers extensive compatibility with multiple data sources, a user-friendly graphical interface, and a strong community supporting big data and transformation capabilities. Spring Cloud Data Flow excels in microservices orchestration with seamless cloud integration, particularly leveraging Kubernetes and flexible architecture for tailored solutions. Its microservices-based approach supports diverse integrations efficiently.

Room for Improvement: Pentaho needs to enhance JSON input handling, better error logging, and improve backward compatibility. Users find cloud integration and handling large datasets challenging, with calls for more connectors and improved documentation. Spring Cloud requires UI improvements, expanded language support, and comprehensive documentation to bolster community support and error handling.

Ease of Deployment and Customer Service: Pentaho enables deployment across on-premises, cloud, and hybrid environments, though cloud integration can be challenging. Community support is active, yet enterprise support varies in responsiveness. Spring Cloud excels in private cloud deployment but faces criticism over community support and complex configurations, with technical support needing improved cloud interaction guidance.

Pricing and ROI: Pentaho provides a cost-effective solution with a free Community Edition and reasonably priced Enterprise Edition, ensuring high ROI by reducing ETL development time. Spring Cloud offers an open-source core with optional paid support, which users find cost-effective due to its flexibility in integration and cloud orchestration capabilities, even as explicit pricing details are less emphasized.

To learn more, read our detailed Pentaho Data Integration and Analytics vs. Spring Cloud Data Flow Report (Updated: March 2026).

Buyer's Guide

Pentaho Data Integration and Analytics vs. Spring Cloud Data Flow

March 2026

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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

Pentaho Data Integration an...

Ranking in Data Integration

8th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

No ranking in other categories

Spring Cloud Data Flow

Ranking in Data Integration

22nd

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (10th)

Mindshare comparison

As of March 2026, in the Data Integration category, the mindshare of Pentaho Data Integration and Analytics is 1.6%, up from 1.4% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.1%, up from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Pentaho Data Integration and Analytics	1.6%
Spring Cloud Data Flow	1.1%
Other	97.3%

Data Integration

Featured Reviews

Michelle Lawson

Principal Software Engineer at a tech vendor with 10,001+ employees

Streamlines complex data workflows and has supported automated customer payment notifications

I haven't used Pentaho Data Integration and Analytics in a couple of years, so I don't know how it can be improved. I was pretty pleased with it and was self-taught on it, working a lot with their team at various times, but they were surprised that I was able to learn it all by myself. The documentation is not bad, and documentation is the main thing that any product can do to make themselves better because the easier it is to find examples of what you're trying to do improves the learning curve. I think it took me the longest to learn how to do the asynchronous processing and have things wait for other things to finish processing before continuing on in the workflow. I choose 8 out of 10 because the one reason that it's been rejected at T-Mobile is that everything has to go through a provisioning process and has to get approved, meaning the actual code base has to be investigated by T-Mobile before they'll allow us to use tools of that nature. For whatever reason, we just haven't been able to get that approval; I don't know if it's on Pentaho Data Integration and Analytics' side or if it's on our side. The more you can make it easier for companies to feel comfortable that your product is secure, robustly tested and bug-free, and free of any other kind of negative hacks, the more quickly it will get accepted.

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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

"It is a lightweight ETL tool that's easy to get started on and connects seamlessly to most commonly used data sources."

"One of the most valuable features is the ability to create many API integrations. I'm always working with advertising agents and using Facebook and Instagram to do campaigns. We use Pentaho to get the results from these campaigns and to create dashboards to analyze the results."

"The most valuable thing for me is that it enables a technical product manager to be able to write ETL jobs themselves, which saves developers time so that they can do more important things."

"No software can give as complete functionality for fulfilling end user requirements as Pentaho."

"It makes it pretty simple to do some fairly complicated things. Both I and some of our other BI developers have made stabs at using, for example, SQL Server Integration Services, and we found them a little bit frustrating compared to Data Integration. So, its ease of use is right up there."

"Provides a good open source option."

"The way it has improved our product is by giving our users the ability to do ad hoc reports, which is very important to our users. We can do predictive analysis on trends coming in for contracts, which is what our product does. The product helps users decide which way to go based on the predictive analysis done by Pentaho. Pentaho is not doing predictions, but reporting on the predictions that our product is doing. This is a big part of our product."

"It is a very good open source ETL tool that's capable of connecting to most databases."

More Pentaho Data Integration and Analytics pros

"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 product is very user-friendly."

"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."

"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."

"This product will assist us in saving costs in many ways: No longer need to continue paying high fees for proprietary software, reduce the number of software engineers needed to support the product, and achieve faster time to market by using this product for our middleware."

More Spring Cloud Data Flow pros

Cons

"As far as I remember, not all connectors worked very well. They can add more connectors and more drivers to the process to integrate with more flows."

"The web interface is rusty, and the biggest problem with Pentaho is debugging and troubleshooting. It isn't easy to build the pipeline incrementally. At least in our case, it's hard to find a way to execute step by step in the debugging mode."

"I also found, in my case, that the statistical data input wasn't working (.sas7bdat input wasn't working)."

"While Pentaho Data Integration is very friendly, it is not very useful when there isn't a lot of data to handle."

"Upgrading the bi-platform is a little pain, but the rest is easy to use and to set up."

"The reporting definitely needs improvement. There are a lot of general, basic features that it doesn't have. A simple feature you would expect a reporting tool to have is the ability to search the repository for a report. It doesn't even have that capability. That's been a feature that we've been asking for since the beginning and it hasn't been implemented yet."

"I could not connect to our Hadoop environment in an easy and flexible way, and it was important to scale our data warehouse."

"The testing and quality could really improve. Every time that there is a major release, we are very nervous about what is going to get broken. We have had a lot of experience with that, as even the latest one was broken. Some basic things get broken. That doesn't look good for Hitachi at all. If there is one place I would advise them to spend some money and do some effort, it is with the quality. It is not that hard to start putting in some unit tests so basic things don't get broken when they do a new release. That just looks horrible, especially for an organization like Hitachi."

More Pentaho Data Integration and Analytics cons

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

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

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

"The visual user interface could use some help; it needs improvement."

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

"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."

"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."

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

More Spring Cloud Data Flow cons

Pricing and Cost Advice

"We are using the Community Edition. We have been trying to use and sell the Enterprise version, but that hasn't been possible due to the budget required for it."

"If a company is looking for an ETL solution and wants to integrate it with their tech stack but doesn't want to spend a bunch of money, Pentaho is a good solution"

"For most development tasks, the Enterprise edition should be sufficient. It depends on the type of support that you require for your production environment."

"I use it because it is free. I download from their page for free. I don't have to pay for a license. With other tools, I have to pay for the licenses. That is why I use Pentaho."

"You don't need the Enterprise Edition, you can go with the Community Edition. That way you can use it for free and, for free, it's a pretty good tool to use."

"We did a two or three-year deal the last time we did it. As compared to other solutions, at least so far in our experience, it has been very affordable. The licensing is by component. So, you need to make sure you only license the components that you really intend to use. I am not sure if we have relicensed after the Hitachi acquisition, but previously, multi-year renewals resulted in a good discount. I'm not sure if this is still the case. We've had the full suite for a lot of years, and there is just the initial cost. I am not aware of any additional costs."

"The price of the regular version is not reasonable and it should be lower."

"I mostly used the open-source version. I didn't work with a license."

More Pentaho Data Integration and Analytics pricing and cost advice

"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."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Educational Organization

Government

Computer Software Company

Financial Services Firm

18%

Computer Software Company

13%

Retailer

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	18
Midsize Enterprise	17
Large Enterprise	31

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	1
Large Enterprise	5

Questions from the Community

Which ETL tool would you recommend to populate data from OLTP to OLAP?

Hi Rajneesh, yes here is the feature comparison between the community and enterprise edition : https://www.hitachivantara.com/en-us/pdf/brochure/leverage-open-source-benefits-with-assurance-of-hita...

See all answers

What do you think can be improved with Hitachi Lumada Data Integrations?

In my opinion, the reporting side of this tool needs serious improvements. In my previous company, we worked with Hitachi Lumada Data Integration and while it does a good job for what it’s worth, ...

See all answers

What do you use Hitachi Lumada Data Integrations for most frequently?

My company has used this product to transform data from databases, CSV files, and flat files. It really does a good job. We were most satisfied with the results in terms of how many people could us...

See all answers

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...

See all answers

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...

See all answers

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

Pentaho Data Integration and Analytics

March 2026

Pentaho Data Integration and Analytics report

Download Pentaho Data Integration and Analytics product report

Buyer's Guide

Spring Cloud Data Flow

February 2026

Download Spring Cloud Data Flow product report

Also Known As

Hitachi Lumada Data Integration, Kettle, Pentaho Data Integration

No data available

Overview

Pentaho Data Integration stands as a versatile platform designed to cater to the data integration and analytics needs of organizations, regardless of their size. This powerful solution is the go-to choice for businesses seeking to seamlessly integrate data from diverse sources, including databases, files, and applications. Pentaho Data Integration facilitates the essential tasks of cleaning and transforming data, ensuring it's primed for meaningful analysis. With a wide array of tools for data mining, machine learning, and statistical analysis, Pentaho Data Integration empowers organizations to glean valuable insights from their data. What sets Pentaho Data Integration apart is its maturity and a vibrant community of users and developers, making it a reliable and cost-effective option. Pentaho Data Integration offers a range of features, including a comprehensive ETL toolkit, data cleaning and transformation capabilities, robust data analysis tools, and seamless deployment options for data integration and analytics solutions, making it a go-to solution for organizations seeking to harness the power of their data.

Hitachi Vantara

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.

Broadcom

Sample Customers

66Controls, Providential Revenue Agency of Ro Negro, NOAA Information Systems, Swiss Real Estate Institute

Information Not Available

Buyer's Guide

Pentaho Data Integration and Analytics vs. Spring Cloud Data Flow

March 2026

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