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 #9 with an average rating of 7.6, while Broadcom is ranked #31 with an average rating of 7.5. Hitachi Vantara holds a 1.7% mindshare in DI, compared to Broadcom’s 1.0% 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 61 Pentaho Data Integration and Analytics reviews

7,262 Views
5,810 Comparison Views

95% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

4,388 Views
2,457 Comparison Views

88% willing to recommend

Pentaho Data Integration an...

Spring Cloud Data Flow

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Executive SummaryUpdated on Jun 3, 2026

Pentaho Data Integration and Spring Cloud Data Flow both compete in the data integration and analytics sector. Pentaho Data Integration appears to have the upper hand due to its user-friendly interface, versatility with data sources, and cost-effective open-source options.

Features: Pentaho Data Integration includes intuitive drag-and-drop workflows, a wide array of plugins, and strong support for big data technologies, making it easy for non-technical users to create data workflows. Spring Cloud Data Flow is known for its orchestration of microservices, seamless Kubernetes integration, and flexible plug-and-play architecture, catering to complex cloud environments.

Room for Improvement:Pentaho Data Integration users report issues with outdated plugins and complex error messages, suggesting enhancements in cloud-native connectors. For Spring Cloud Data Flow, users request an improved user interface, better documentation, and smoother Kubernetes interactions, calling for more developed monitoring tools.

Ease of Deployment and Customer Service:Pentaho Data Integration can be deployed on-premises, hybrid, or cloud, offering flexibility. However, its customer service from Hitachi receives mixed feedback. Spring Cloud Data Flow excels in cloud integrations but has challenges with community-driven customer support, affecting more complex deployment scenarios.

Pricing and ROI:Pentaho Data Integration's Community Edition is free, making it attractive for budget-conscious organizations, delivering substantial ROI through reduced development time. Spring Cloud Data Flow provides value primarily as an open-source solution, with extra costs for enterprise support.

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

Buyer's Guide

Pentaho Data Integration and Analytics vs. Spring Cloud Data Flow

August 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

9th

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

31st

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (17th)

Mindshare comparison

As of August 2026, in the Data Integration category, the mindshare of Pentaho Data Integration and Analytics is 1.7%, down from 1.7% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.0%, down from 1.2% 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	1.7%
Spring Cloud Data Flow	1.0%
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

"If we didn't have this solution, we wouldn't be able to manage our workload or generate the volume of reporting that we currently do."

"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 have been able to expose data services through the use of CDA relying on the same database as the reporting tools, thus avoiding inconsistencies among the data shown by reports and data acquired by external systems."

"The solution is easy to set up, very intuitive, clear to understand and easy to maintain."

"We're using the PDI and the repository function, and they give us the ability to easily generate reporting and output, and to access data. We also like the ability to schedule."

"We can schedule job execution in the BA Server, which is the front-end product we're using right now. That scheduling interface is nice."

"The fact that it enables us to leverage metadata to automate data pipeline templates and reuse them is definitely one of the features that we like the best. The metadata injection is helpful because it reduces the need to create and maintain additional ETLs. If we didn't have that feature, we would have lots of duplicated ETLs that we would have to create and maintain. The data pipeline templates have definitely been helpful when looking at productivity and costs."

"I would say this is the best ETL tool in the market, considering this is open source and ease to use, very nice GUI."

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 dashboards in Spring Cloud Dataflow are quite valuable."

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

"Overall, Spring Cloud Data Flow is a really good solution and a lot cheaper than a lot of infrastructure provided by big companies like Google or Amazon."

"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 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."

More Spring Cloud Data Flow pros

Cons

"I was not happy with the Pentaho Report Designer because of the way it was set up. There was a zone and, under it, another zone, and under that another one, and under that another one. There were a lot of levels and places inside the report, and it was a little bit complicated. You have to search all these different places using a mouse, clicking everywhere... each report is coded in a binary file... You cannot search with a text search tool..."

"The only complaint that I have with Pentaho has been with scaling."

"Should provide additional control for the data warehouse"

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

"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."

"I was not happy with the Pentaho Report Designer because of the way it was set up."

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

"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."

More Pentaho Data Integration and Analytics cons

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

"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."

"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."

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

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

"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

"When we first started with it, it was much cheaper. It has gone up drastically, especially since Hitachi bought out Pentaho."

"The pricing has been pretty good. I'm used to using everything open-source or freeware-based. I understand that organizations need to make sure that the solutions are secure, and that's basically where I hit a roadblock in my current organization. They needed to ensure that we had a license and we had a secure way of accessing it so that no outside parties could get access to our data, but in terms of pricing, considering how much other teams are spending on cloud solutions or even their existing solutions, its price point is pretty good. At this time, there are no additional costs. We just have the licensing fees."

"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."

"Sometimes we provide the licenses or the customer can procure their own licenses. Previously, we had an enterprise license. Currently, we are on a community license as this is adequate for our needs."

"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."

"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."

"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."

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."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Construction Company

Educational Organization

Outsourcing Company

Financial Services Firm

17%

Computer Software Company

10%

Retailer

Outsourcing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	18
Midsize Enterprise	17
Large Enterprise	32

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

July 2026

Pentaho Data Integration and Analytics report

Download Pentaho Data Integration and Analytics product report

Buyer's Guide

Spring Cloud Data Flow

July 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 and Analytics offers an intuitive platform for data workflows, enabling users to easily manage ETL processes across diverse data formats, ensuring seamless automation and development.

With its drag-and-drop interface, Pentaho allows for efficient ETL workflows without extensive coding. It supports a multitude of data formats and sources such as SQL, NoSQL, Hadoop, CSV, and JSON. Advanced features like metadata injection and API integration enable seamless automation. However, improvements in big data performance, better cloud service integration, and enhanced real-time processing capabilities can enhance user experience. Additional connectors and improved documentation are sought after by many. Providing support for more programming languages and optimizing memory usage also presents opportunities for enhancement.

What are the key features of Pentaho Data Integration and Analytics?

Drag-and-Drop Interface: Simplifies building workflows without coding.
Broad Data Support: Accommodates SQL, NoSQL, Hadoop, CSV, and JSON.
Advanced Automation: Leverages metadata injection and API integration.
Cost-Effectiveness: Offers value with comprehensive big data support.

What benefits should be evaluated in Pentaho reviews?

Versatility: Supports both on-premises and cloud solutions.
Data Integration: Facilitates seamless connection of disparate data sources.
Transparency: Enhances data management and reporting.
Scalability: Adapts to the growing data needs of organizations.

Pentaho is employed across finance, healthcare, and retail industries for ETL processes. It's instrumental in integrating data from ERP, SAP systems, Excel, and APIs to develop comprehensive reports and data models. Companies rely on its capabilities for both on-premises and cloud deployments, improving data transparency and management.

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

August 2026

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