Pentaho Data Integration and Analytics vs Spring Cloud Data Flow comparison

Hitachi Vantara and VMware are both solutions in the Data Integration category. Hitachi Vantara is ranked #19 with an average rating of 7.7, while VMware is ranked #21 with an average rating of 7.8. Hitachi Vantara holds a 1.8% mindshare in DI, compared to VMware’s 1.2% mindshare. Additionally, 94% of Hitachi Vantara users are willing to recommend the solution, compared to 88% of VMware users who would recommend it.

Pentaho Data Integration an...

Read 53 Pentaho Data Integration and Analytics reviews

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1,021 Comparison Views

94% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

1,322 Views
923 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: June 2025).

Buyer's Guide

Pentaho Data Integration and Analytics vs. Spring Cloud Data Flow

June 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

Pentaho Data Integration an...

Ranking in Data Integration

19th

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Spring Cloud Data Flow

Ranking in Data Integration

21st

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (9th)

Mindshare comparison

As of June 2025, in the Data Integration category, the mindshare of Pentaho Data Integration and Analytics is 1.8%, up from 0.7% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.2%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

Aqeel UR Rehman

BI Analyst at a computer software company with 51-200 employees

Transform data efficiently with rich features but there's challenges with large datasets

Currently, I am using Pentaho Data Integration for transforming data and then loading it into different platforms. Sometimes, I use it in conjunction with AWS, particularly S3 and Redshift, to execute the copy command for data processing Pentaho Data Integration is easy to use, especially when…

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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

"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."

"Provides a good open source option."

"The abstraction is quite good."

"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."

"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."

"Lumada has allowed us to interact with our employees more effectively and compensate them properly. One of the cool things is that we use it to generate commissions for our salespeople and bonuses for our warehouse people. It allows us to get information out to them in a timely fashion. We can also see where they're at and how they're doing."

"Sometimes, it took a whole team about two weeks to get all the data to prepare and present it. After the optimization of the data, it took about one to two hours to do the whole process. Therefore, it has helped a lot when you talk about money, because it doesn't take a whole team to do it, just one person to do one project at a time and run it when you want to run it. So, it has helped a lot on that side."

"We use Lumada’s ability to develop and deploy data pipeline templates once and reuse them. This is very important. When the entire pipeline is automated, we do not have any issues in respect to deployment of code or with code working in one environment but not working in another environment. We have saved a lot of time and effort from that perspective because it is easy to build ETL pipelines."

More Pentaho Data Integration and Analytics pros

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

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

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

Cons

"Some of the scheduling features about Lumada drive me buggy. The one issue that always drives me up the wall is when Daylight Savings Time changes. It doesn't take that into account elegantly. Every time it changes, I have to do something. It's not a big deal, but it's annoying."

"Since Hitachi took over, I don't feel that the documentation is as good within the solution. It used to have very good help built right in."

"Lumada could have more native connectors with other vendors, such as Google BigQuery, Microsoft OneDrive, Jira systems, and Facebook or Instagram. We would like to gather data from modern platforms using Lumada, which is a better approach. As a comparison, if you open Power BI to retrieve data, then you can get data from many vendors with cloud-native connectors, such as Azure, AWS, Google BigQuery, and Athena Redshift. Lumada should have more native connectors to help us and facilitate our job in gathering information from these new modern infrastructures and tools."

"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."

"I would like to see improvement when it comes to integrating structured data with text data or anything that is unstructured. Sometimes we get all kinds of different files that we need to integrate into the warehouse."

"Communicating with the vendor is challenging, and this hinders its performance in free tool setups."

"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."

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

More Pentaho Data Integration and Analytics cons

"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."

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

"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 is not an easy-to-use tool, so 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."

"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

"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."

"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."

"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."

"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."

"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."

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

"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

22%

Computer Software Company

14%

Government

Manufacturing Company

Financial Services Firm

26%

Computer Software Company

17%

Retailer

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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...

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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...

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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Compared 6% of the time

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Compared 5% of the time

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Product Reports

Buyer's Guide

Pentaho Data Integration and Analytics

May 2025

Pentaho Data Integration and Analytics report

Download Pentaho Data Integration and Analytics product report

Buyer's Guide

Spring Cloud Data Flow

May 2025

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.

VMware

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

June 2025

Free Report: Pentaho Data Integration and Analytics vs. Spring Cloud Data Flow

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