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

"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."

"Provides a good open source option."

"The solution offers features for data integration and migration. Pentaho Data Integration and Analytics allows the integration of multiple data sources into one. The product is user-friendly and intuitive to use for almost any business."

"Pentaho Data Integration and Analytics has positively impacted my organization by saving costs, managing large data sets, and integrating multiple sources."

"Pentaho Data Integration and Analytics has had a notably positive impact on my organization, enabling us to complete several projects efficiently."

"Its drag-and-drop interface lets me and my team implement all the solutions that we need in our company very quickly. It's a very good tool for that."

"Data transformation within Pentaho is a nice feature that they have and that I value."

"We also haven't had to create any custom Java code. Almost everywhere it's SQL, so it's done in the pipeline and the configuration. That means you can offload the work to people who, while they are not less experienced, are less technical when it comes to logic."

More Pentaho Data Integration and Analytics pros

"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 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 most valuable feature is real-time streaming."

"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 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."

Cons

"There is not a data quality or MDM solution in the Pentaho DI suite."

"It's not very stable, at least not in the case of the community edition. I'm working with the community edition right now and I think perhaps it is because of that it is not very stable, it causes the system to sometimes hang. I'm not sure if this is the case for pair tiers."

"I'm still in the very recent stage concerning Pentaho Data Integration, but it can't really handle what I describe as "extreme data processing" i.e. when there is a huge amount of data to process. That is one area where Pentaho is still lacking."

"If you develop it on MacBook, it'll be quite a hassle."

"In terms of improvements, while creating on a remote service, we face challenges related to limited memory, which calls for optimization."

"One thing I wish was better about Pentaho Data Integration and Analytics is its performance, as it sometimes gets intensive on the CPU standpoint, taking a lot of memory in some cases, especially when dealing with big data sets."

"In terms of the flexibility to deploy in any environment, such as on-premise or in the cloud, we can do the cloud deployment only through virtual machines. We might also be able to work on different environments through Docker or Kubernetes, but we don't have an Azure app or an AWS app for easy deployment to the cloud. We can only do it through virtual machines, which is a problem, but we can manage it. We also work with Databricks because it works with Spark. We can work with clustered servers, and we can easily do the deployment in the cloud. With a right-click, we can deploy Databricks through the app on AWS or Azure cloud."

"One thing that I don't like, just a little, is the backward compatibility."

More Pentaho Data Integration and Analytics cons

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

"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."

"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."

"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."

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

Pricing and Cost Advice

"The solution reduced our ETL development time by a lot because a whole project used to take about a month to get done previously. After having Lumada, it took just a week. For a big company in Brazil, it saves a team at least $10,000 a month."

"You need to go through the paid version to have Hitachi Lumada specialized support. However, if you are using the free version, then you will have only the community support. You will depend on the releases from Hitachi to solve some problem or questions that you have, such as bug fixes. You will need to wait for the newest versions or releases to solve these types of problems."

"I believe the pricing of the solution is more affordable than the competitors"

"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."

"It does seem a bit expensive compared to the serverless product offering. Tools, such as Server Integration Services, are "almost" free with a database engine. It is comparable to products like Alteryx, which is also very expensive."

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

"I primarily work on the Community Version, which is available to use free of charge."

"I think Lumada's price is fair compared to some of the others, like BusinessObjects, which is was the other thing that I used at my previous job. BusinessObject's price was more reasonable before SAP acquired it. They jacked the price up significantly. Oracle's OBIEE tool was also prohibitively expensive."

More Pentaho Data Integration and Analytics pricing and cost advice

"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

Financial Services Firm

12%

Educational Organization

10%

Government

Manufacturing 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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