IBM Cloud Pak for Integration vs Pentaho Data Integration and Analytics comparison

IBM and Hitachi Vantara are both solutions in the Cloud Data Integration category. Additionally, 100% of IBM users are willing to recommend the solution, compared to 95% of Hitachi Vantara users who would recommend it.

IBM Cloud Pak for Integration

Read 5 IBM Cloud Pak for Integration reviews

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809 Comparison Views

100% willing to recommend

Pentaho Data Integration an...

Read 61 Pentaho Data Integration and Analytics reviews

6,686 Views
5,349 Comparison Views

95% willing to recommend

IBM Cloud Pak for Integration

Pentaho Data Integration an...

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Executive Summary

We performed a comparison between IBM Cloud Pak for Integration and Pentaho Data Integration and Analytics based on real PeerSpot user reviews.

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To learn more, read our detailed Cloud Data Integration Report (Updated: June 2026).

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Cloud Data Integration

June 2026

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Helped 902,988 peers since 2012

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

IBM Cloud Pak for Integration

Average Rating

8.6

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

API Management (28th), Cloud Data Integration (20th)

Pentaho Data Integration an...

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Data Integration (9th)

Featured Reviews

Igor Khalitov

Owner/Full Stack Software Engineer at Maraphonic, Inc.

Manages APIs and integrates microservices with redirection feature

IBM Cloud Pak for Integration includes monitoring capabilities to track the performance and health of your integrations. You can quickly roll back to a previous version if an issue arises. Additionally, it supports incremental deployments, allowing you to shift traffic to a new version of an API gradually. For example, you can start by directing 10% of traffic to the new version while the rest continue using the legacy version. If everything works as expected, you can gradually increase the traffic to the new version over time. IBM Cloud Pak for Integration has a client base that includes numerous organizations using AI and machine learning technologies. We leverage an open-source machine learning framework and integrate it with Kafka to help create and manage various products and data retrieval processes. For companies with private data, the framework first retrieves relevant data from a GitHub database, which is then combined with the final request before being sent to a language model like GPT. This ensures that the language model uses your specific data to generate responses. Kafka plays a key role by streaming real-time data from file systems and databases like Oracle and Microsoft SQL. This data is published to Kafka topics, then vectorized and used with artificial intelligence to enhance the overall process. It's like an old-fashioned approach. The best way is to redesign it with products such as Kafka. Overall, I rate the solution an eight out of ten.

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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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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The most preferable aspect would be the elimination of the command, which was a significant improvement. In the past, it was a challenge, but now we can proceed smoothly with the implementation of our policies and everything is managed through JCP. It's still among the positive aspects, and it's a valuable feature."

"Cloud Pak for Integration is definitely scalable. That is the most important criteria."

"In general, the solution works very, very well."

"The most valuable aspect of the Cloud Pak, in general, is the flexibility that you have to use the product."

"It is a stable solution."

"Redirection is a key feature. It helps in managing multiple microservices by centralizing control and access."

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

"All you need is a balance of experienced users and new trainees to get going."

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

"The graphical nature of the development interface is most useful because we've got people with quite mixed skills in the team. We've got some very junior, apprentice-level people, and we've got support analysts who don't have an IT background. It allows us to have quite complicated data flows and embed logic in them. Rather than having to troll through lines and lines of code and try and work out what it's doing, you get a visual representation, which makes it quite easy for people with mixed skills to support and maintain the product. That's one side of it."

"Running itself with the ETL was very fast; it makes it so that it is very easy to transform the information we have, and we found that very useful."

"Pentaho Kettle has a very intuitive and easy to use graphical user interface (GUI) and it is possible to understand how to develop an ETL solution even when using it for the first time."

"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."

"Pentaho Data Integration and Analytics has positively impacted my organization because it meant we didn't have to write a lot of custom API back-end processing logic; it did the majority of that heavy lifting for us."

More Pentaho Data Integration and Analytics pros

Cons

"The pricing can be improved."

"The initial setup is not easy."

"Setting up Cloud Pak for Integration is relatively complex. It's not as easy because it has not yet been fully integrated. You still have some products that are still not containerized, so you still have to run them on a dedicated VM."

"What needs to be improved is the restriction that they have on the product."

"Enterprise bots are needed to balance products like Kafka and Confluent."

"Its queuing and messaging features need improvement."

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

"Its basic functionality doesn't need a whole lot of change. There could be some improvement in the consistency of the behavior of different transformation steps. The software did start as open-source and a lot of the fundamental, everyday transformation steps that you use when building ETL jobs were developed by different people. It is not a seamless paradigm. A table input step has a different way of thinking than a data merge step."

"I work with different databases. I would like to work with more connectors to new databases, e.g., DynamoDB and MariaDB, and new cloud solutions, e.g., AWS, Azure, and GCP. If they had these connectors, that would be great. They could improve by building new connectors. If you have native connections to different databases, then you can make instructions more efficient and in a more natural way. You don't have to write any scripts to use that connector."

"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."

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

"It could be better integrated with programming languages, like Python and R. Right now, if I want to run a Python code on one of my ETLs, it is a bit difficult to do. It would be great if we have some modules where we could code directly in a Python language. We don't really have a way to run Python code natively."

"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."

"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

Pricing and Cost Advice

"It is an expensive solution."

"The solution's pricing model is very flexible."

"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."

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

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

"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."

"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."

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

"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."

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

More Pentaho Data Integration and Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Government

11%

Manufacturing Company

Construction Company

Financial Services Firm

16%

Educational Organization

Construction Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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

Questions from the Community

What needs improvement with IBM Cloud Pak for Integration?

Enterprise bots are needed to balance products like Kafka and Confluent.

See all answers

What is your primary use case for IBM Cloud Pak for Integration?

It manages APIs and integrates microservices at the enterprise level. It offers a range of capabilities for handling APIs, microservices, and various integration needs. The platform supports thousa...

See all answers

What advice do you have for others considering IBM Cloud Pak for Integration?

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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

Comparisons

AWS Glue vs IBM Cloud Pak for Integration

Compared 13% of the time

AVAP Sphere vs IBM Cloud Pak for Integration

Compared 11% of the time

IBM API Connect vs IBM Cloud Pak for Integration

Compared 10% of the time

IBM App Connect vs IBM Cloud Pak for Integration

Compared 9% of the time

IBM DataPower Gateway vs IBM Cloud Pak for Integration

Compared 8% of the time

More IBM Cloud Pak for Integration Competitors

Airbyte Cloud vs Pentaho Data Integration and Analytics

Compared 11% of the time

Informatica PowerCenter vs Pentaho Data Integration and Analytics

Compared 7% of the time

Oracle Data Integrator (ODI) vs Pentaho Data Integration and Analytics

Compared 7% of the time

SSIS vs Pentaho Data Integration and Analytics

Compared 7% of the time

StreamSets vs Pentaho Data Integration and Analytics

Compared 5% of the time

More Pentaho Data Integration and Analytics Competitors

Product Reports

Buyer's Guide

API Management

June 2026

Download IBM Cloud Pak for Integration product report

Buyer's Guide

Pentaho Data Integration and Analytics

June 2026

Pentaho Data Integration and Analytics report

Download Pentaho Data Integration and Analytics product report

Also Known As

No data available

Hitachi Lumada Data Integration, Kettle, Pentaho Data Integration

Overview

IBM Cloud Pak for Integration offers multi-cloud management and automation, focusing on connecting core systems for seamless integration using advanced technologies and efficient API management.

IBM Cloud Pak for Integration provides flexibility, automation, and accounting tools on the OpenShift Container Platform, easing license and management. Among its notable features are effective streaming capabilities, simplified policy implementation via JCP, and enhanced control with redirection, particularly beneficial for microservices management. Its stability and practical container management are major advantages. However, limitations include exclusive IBM product deployment over OpenShift and complex initial setup. Users seek better pricing, enhanced streaming features, improved queuing and messaging, and integration with monitoring tools. Enhanced enterprise bots are needed for balance with Kafka and Confluent.

What are IBM Cloud Pak for Integration's key features?

Flexibility: Supports multi-cloud management and automation for seamless integration.
Streaming: Effective streaming feature for data processing and policy implementation.
Redirection: Enhances control and access for microservices management.
OpenShift Platform: Simplifies licensing and management with container technology.

What benefits should users look for in reviews?

Efficiency: Simplified policy implementation and automation reduce operational challenges.
Control: Enhanced management of microservices and APIs for streamlined operations.
Stability: Robust container management for consistent performance.
Integration: Supports integration with multiple technologies like Kafka and DataPower.

Implemented across industries like travel and banking, IBM Cloud Pak for Integration aids in connecting core systems and enables effective automation and API management. It supports data conversion, format alterations, and comprehensive management of numerous APIs, providing deployment options based on specific needs.

IBM

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

Sample Customers

CVS Health Corporation

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

Buyer's Guide

Cloud Data Integration

June 2026

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