Pentaho Data Integration and Analytics vs Spring Cloud Data Flow comparison

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Hitachi Vantara and Broadcom are both solutions in the Data Integration category. Hitachi Vantara is ranked #8 with an average rating of 7.7, while Broadcom is ranked #33 with an average rating of 8.0. Hitachi Vantara holds a 1.9% 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 61 Pentaho Data Integration and Analytics reviews

10,001 Views
7,901 Comparison Views

95% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

5,525 Views
3,205 Comparison Views

88% willing to recommend

Pentaho Data Integration an...

Spring Cloud Data Flow

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Executive SummaryUpdated on Nov 8, 2026

Pentaho Data Integration and Analytics and Spring Cloud Data Flow are two leading solutions in the data integration and analytics industry. While Pentaho is favored for its user satisfaction with pricing and ease of use, Spring Cloud Data Flow is commended for its advanced features and performance.

Features: Pentaho Data Integration and Analytics is known for its user-friendly drag-and-drop interface, versatile big data integration, and community support. It supports rapid prototyping and handles diverse ETL workloads efficiently. Spring Cloud Data Flow, however, offers a plug-and-play architecture, excels in microservices orchestration, and provides seamless integration, particularly with cloud environments and real-time streaming capabilities.

Room for Improvement: Pentaho could benefit from better documentation, enhanced performance for large data sets, and additional cloud connectors. Spring Cloud Data Flow users have noted the need for improved documentation, more robust community support, and simpler configuration with enhanced dashboard functionalities.

Ease of Deployment and Customer Service: Pentaho Data Integration offers flexibility with varied deployment options in both on-premises and cloud environments, though customer service experiences differ especially between community and paid versions. Spring Cloud Data Flow is effective in private environments but faces challenges with limited community support, impacting troubleshooting and issue resolution.

Pricing and ROI: Pentaho is celebrated for affordability, particularly its free community edition delivering strong performance. It often provides high ROI by reducing development time. Spring Cloud Data Flow is cost-effective as an open-source solution, though potentially incurring higher costs with advanced support. Its focus on simplifying development translates to time savings and improved operational efficiency.

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

Buyer's Guide

Pentaho Data Integration and Analytics vs. Spring Cloud Data Flow

November 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

33rd

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (17th)

Mindshare comparison

As of November 2026, in the Data Integration category, the mindshare of Pentaho Data Integration and Analytics is 1.9%, up from 1.6% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.1%, down from 1.1% 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	1.9%
Spring Cloud Data Flow	1.1%
Other	97.0%

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

"We have seen at least 30% savings in terms of effort, which has helped us to price our service and products more aggressively in the market and win more clients."

"We are very productive today thanks to that piece of software integration our data and the platform serving the processed data to our users."

"I can create faster instructions than writing with SQL or code. Also, I am able to do some background control of the data process with this tool. Therefore, I use it as an ELT tool. I have a station area where I can work with all the information that I have in my production databases, then I can work with the data that I created."

"Easy to use, support for all databases (jdbc and odbc connection), xls, csv, files, txt, SAS, R."

"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's a low-code solution is valuable. It's good for more junior people who may not be as experienced with programming."

"You can get ETL, reporting, analysis, and analytics in a single shop."

"After using this product, we could do some of the things much faster than before."

More Pentaho Data Integration and Analytics pros

"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."

"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 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 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 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 dashboards in Spring Cloud Dataflow are quite valuable."

"The product is very user-friendly."

More Spring Cloud Data Flow pros

Cons

"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 product itself is great, the biggest downside in my opinion is that it is hard to find (hire) people with expertise."

"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 would like to have more languages/scripts supported in user-defined classes."

"I think Pentaho Data Integration and Analytics needs additional plugins for the market, and for some specific tasks it is very difficult."

"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..."

"When dealing with substantial data volumes from cloud systems, performance can become an issue; even using the Enterprise Edition, the time required for executing particular pipeline tasks is notably high compared to other ETL tools such as ADF, DataBricks, or SSIS."

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."

"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."

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

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

"The documentation on offer is not that good."

"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."

More Spring Cloud Data Flow cons

Pricing and Cost Advice

"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"

"There is a good open source option (Community Edition)."

"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 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."

"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 cost of these types of solutions are expensive. So, we really appreciate what we get for our money. Though, we don't think of the solution as a top-of-the-line solution or anything like that."

"There was a cost analysis done and Pentaho did favorably in terms of cost."

More Pentaho Data Integration and Analytics pricing and cost advice

"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."

"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

11%

Outsourcing Company

11%

Construction Company

Educational Organization

Financial Services Firm

15%

Outsourcing Company

Computer Software Company

Comms Service Provider

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

Comparisons

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Compared 8% of the time

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Compared 7% of the time

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Compared 7% of the time

Airbyte Cloud vs Pentaho Data Integration and Analytics

Compared 7% of the time

StreamSets vs Pentaho Data Integration and Analytics

Compared 5% of the time

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Apache Flink vs Spring Cloud Data Flow

Compared 6% of the time

TIBCO Spotfire vs Spring Cloud Data Flow

Compared 6% of the time

Cloudera DataFlow vs Spring Cloud Data Flow

Compared 5% of the time

StreamSets vs Spring Cloud Data Flow

Compared 4% of the time

More Spring Cloud Data Flow Competitors

Product Reports

Buyer's Guide

Pentaho Data Integration and Analytics

October 2026

Pentaho Data Integration and Analytics report

Download Pentaho Data Integration and Analytics product report

Buyer's Guide

Spring Cloud Data Flow

October 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

November 2026

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

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