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

1,882 Views
715 Comparison Views

100% willing to recommend

Pentaho Data Integration an...

Read 60 Pentaho Data Integration and Analytics reviews

5,702 Views
4,562 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.

Find out in this report how the two Cloud Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed IBM Cloud Pak for Integration vs. Pentaho Data Integration and Analytics Report (Updated: April 2026).

Buyer's Guide

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

April 2026

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Helped 894,738 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 (27th), Cloud Data Integration (19th)

Pentaho Data Integration an...

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Data Integration (7th)

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."

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

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

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

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

"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."

"The solution has a free to use community version."

"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 can do predictive analysis on trends coming in for contracts, which is what our product does. The product helps users decide which way to go based on the predictive analysis done by Pentaho. Pentaho is not doing predictions, but reporting on the predictions that our product is doing. This is a big part of our product."

"The abstraction is quite good."

"Pentaho Data Integration and Analytics is a great solution to accomplish big things in a very short time."

"Pentaho Data Integration is quite simple to learn, and there is a lot of information available online."

"The amount of data that it loads and processes is good."

"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."

"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."

More Pentaho Data Integration and Analytics pros

Cons

"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."

"The pricing can be improved."

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

"Its queuing and messaging features need improvement."

"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."

"A big problem after deploying something that we do in Lumada is with Git. You get a binary file to do a code review, so if you need to do a review, you have to take pictures of the screen to show each step."

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

"Support for common Hadoop utilities can be expanded, such as bulk load with composite row keys for HBase, and include drivers for Impala out-of-the-box."

"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."

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

"I experience difficulties when handling millions of rows, as the data movement from one source to another becomes challenging."

"Pentaho Dashboard Designer - needs an improvement on the various features of the Dashboards, since there are CTools available and which help to fulfil the gaps, but it needs developers involvement."

"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."

More Pentaho Data Integration and Analytics cons

Pricing and Cost Advice

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

"It is an expensive solution."

"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."

"The price of the regular version is not reasonable and it should be lower."

"For most development tasks, the Enterprise edition should be sufficient. It depends on the type of support that you require for your production environment."

"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"

"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 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."

"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 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."

More Pentaho Data Integration and Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Government

11%

Manufacturing Company

Insurance Company

Financial Services Firm

15%

Educational Organization

Government

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	31

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...

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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

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Compared 10% of the time

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Compared 7% of the time

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Compared 12% of the time

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Compared 8% of the time

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

Compared 7% of the time

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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

API Management

May 2026

Download IBM Cloud Pak for Integration product report

Buyer's Guide

Pentaho Data Integration and Analytics

April 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

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

April 2026

Free Report: IBM Cloud Pak for Integration vs. Pentaho Data Integration and Analytics

Find out what your peers are saying about IBM Cloud Pak for Integration vs. Pentaho Data Integration and Analytics and other solutions. Updated: April 2026.

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