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

IBM and Hitachi Vantara are both solutions in the Data Integration category. IBM is ranked #16 with an average rating of 8.2, while Hitachi Vantara is ranked #22 with an average rating of 7.7. IBM holds a 1.8% mindshare in DI, compared to Hitachi Vantara’s 1.6% mindshare. Additionally, 86% of IBM users are willing to recommend the solution, compared to 94% of Hitachi Vantara users who would recommend it.

IBM Cloud Pak for Data

Read 13 IBM Cloud Pak for Data reviews

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1,932 Comparison Views

86% willing to recommend

Pentaho Data Integration an...

Read 53 Pentaho Data Integration and Analytics reviews

2,102 Views
1,065 Comparison Views

94% willing to recommend

IBM Cloud Pak for Data

Pentaho Data Integration an...

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Executive SummaryUpdated on Dec 19, 2024

Pentaho Data Integration and Analytics and IBM Cloud Pak for Data compete in the data integration and analytics sector. Pentaho is particularly noted for its speed and adaptability, while IBM stands out for its comprehensive capabilities and AI-driven insights. Pentaho seems to have the upper hand due to its cost-effectiveness and adaptability.

Features: Pentaho Data Integration offers an intuitive system that easily integrates with various data sources, excellent data transformation features, and a customizable interface. It facilitates rapid development and effective visualization of diverse data formats. IBM Cloud Pak for Data provides robust data preparation, integration, and governance features along with the versatility of the Watson suite for AI insights, making it suitable for large enterprises seeking comprehensive solutions.

Room for Improvement: Pentaho could improve performance in real-time processing, debugging feedback, and version compatibility. It lacks native support for some modern databases and big data platforms. IBM could benefit from simplified deployment options, more connectors, improved interface responsiveness, and reduced complexity and cost to be more appealing to smaller organizations.

Ease of Deployment and Customer Service: Pentaho Data Integration excels in on-premises and hybrid cloud deployments, supported by an active community and online resources, though official support can be slow. IBM Cloud Pak for Data is strong in public and hybrid cloud settings, with robust technical support, but users often find deployment complex. User satisfaction on support responsiveness varies between the products.

Pricing and ROI: Pentaho offers a free Community Edition and an affordable Enterprise Edition, providing significant value and reducing entry barriers for ETL development. Its open-source nature allows for notable savings. IBM Cloud Pak for Data, while offering advanced features, is seen as expensive and geared towards larger enterprises with substantial budgets.

To learn more, read our detailed IBM Cloud Pak for Data vs. Pentaho Data Integration and Analytics Report (Updated: April 2025).

Buyer's Guide

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

April 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

IBM Cloud Pak for Data

Ranking in Data Integration

16th

Average Rating

7.8

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Virtualization (3rd)

Pentaho Data Integration an...

Ranking in Data Integration

22nd

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2025, in the Data Integration category, the mindshare of IBM Cloud Pak for Data is 1.8%, up from 1.7% compared to the previous year. The mindshare of Pentaho Data Integration and Analytics is 1.6%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

Michelle Leslie

Data asset management engineer at a tech services company with 1-10 employees

Starts strong with data management capabilities but needs a demo database

What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated. There are so many components to data management, and more often than not, people understand one thing really well. They may understand DataStage and how to move data around, but they do not see the impact of moving data incorrectly. They also do not see the impact of everyone understanding a piece of data in the same way. I would love Cloud Pak to come with a demo database that illustrates the different components of data management in a logical way, so I can see the whole picture instead of just the area I'm specializing in. It would be great if Cloud Pak, from a data modeling point of view, allowed us to import our PDMs, for example. It would be ideal to import and create business terms in Cloud Pak. The PEA would be great to create the technical data. The association between the business and the technical metadata could then be automated by pulling it through from your ACE models. The data modeling component is available in Cloud Pak. Additionally, when it comes to Cloud Pak, even though it has the NextGen DataStage built into it, there is Cloud Pak for data integration as well. Currently, I do not think we have a full enough understanding of how CP4D and CP4I can enhance each other.

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Ryan Ferdon

Senior Data Engineer at Burgiss

Low-code makes development faster than with Python, but there were caching issues

If you're working with a larger data set, I'm not so sure it would be the best solution. The larger things got the slower it was. It was kind of buggy sometimes. And when we ran the flow, it didn't go from a perceived start to end, node by node. Everything kicked off at once. That meant there were times when it would get ahead of itself and a job would fail. That was not because the job was wrong, but because Pentaho decided to go at everything at once, and something would process before it was supposed to. There were nodes you could add to make sure that, before this node kicks off, all these others have processed, but it was a bit tedious. There were also caching issues, and we had to write code to clear the cache every time we opened the program, because the cache would fill up and it wouldn't run. I don't know how hard that would be for them to fix, or if it was fixed in version 10. Also, the UI is a bit outdated, but I'm more of a fan of function over how something looks. One other thing that would have helped with Pentaho was documentation and support on the internet: how to do things, how to set up. I think there are some sites on how to install it, and Pentaho does have a help repository, but it wasn't always the most useful.

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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

"IBM Watson Catalog and data pipelines are the most valuable features of the solution."

"The most valuable features of IBM Cloud Pak for Data are the Watson Studio, where we can initiate more groups and write code. Additionally, Watson Machine Learning is available with many other services, such as APIs which you can plug the machine learning models."

"I love the way that I can start at a very basic level with my data management journey by capturing my policies, justifying my data, and putting them into different categories to say this is data relating to individuals, for example, or data relating to geography."

"You can model the data there, connect the data models with the business processes and create data lineage processes."

"The most valuable features are data virtualization and reporting."

"DataStage allows me to connect to different data sources."

"What I found most helpful in IBM Cloud Pak for Data is containerization, which means it's easy to shift and leave in terms of moving to other clouds. That's an advantage of IBM Cloud Pak for Data."

"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."

More IBM Cloud Pak for Data pros

"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."

"Provides a good open source option."

"It's my understanding that the product can scale."

"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."

"It has a really friendly user interface, which is its main feature. The process of automating or combining SQL code with some databases and doing the automation is great and really convenient."

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

"I can use Python, which is open-source, and I can run other scripts, including Linux scripts. It's user-friendly for running any object-based language. That's a very important feature because we live in a world of open-source."

"The area where Lumada has helped us is in the commercial area. There are many extractions to compose reports about our sales team performance and production steps. Since we are using Lumada to gather data from each industry in each country. We can get data from Argentina, Chile, Brazil, and Colombia at the same time. We can then concentrate and consolidate it in only one place, like our data warehouse. This improves our production performance and need for information about the industry, production data, and commercial data."

More Pentaho Data Integration and Analytics pros

Cons

"The tool depends on the control plane, an OpenShift container platform utilized as an orchestration layer...So, we have communicated this issue to IBM and asked if it is feasible to adapt the solution to work on a Kubernetes platform that we support."

"The setup cost is very expensive. The cost depends on the pieces of the solution I'm using, how much data I have, and whether it's on the cloud or on-prem."

"The solution's catalog searching or map search needs to be improved."

"One thing that bugs me is how much infrastructure Cloud Pak requires for the initial deployment. It doesn't allow you to start small. The smallest permitted deployment is too big. It's a huge problem that prevents us from implementing the solution in many scenarios."

"One challenge I'm facing with IBM Cloud Pak for Data is native features have been decommissioned, such as XML input and output. Too many changes have been made, and my company has around one hundred thousand mappings, so my team has been putting more effort into alternative ways to do things. Another area for improvement in IBM Cloud Pak for Data is that it's more complicated to shift from on-premise to the cloud. Other vendors provide secure agents that easily connect with your existing setup. Still, with IBM Cloud Pak for Data, you have to perform connection migration steps, upgrade to the latest version, etc., which makes it more complicated, especially as my company has XML-based mappings. Still, the XML input and output capabilities of IBM Cloud Pak for Data have been discontinued, so I'd like IBM to bring that back."

"The technical support could be a little better."

"There is a solution that is part of IBM Cloud Pak for Data called Watson OpenScale. It is used to monitor the deployed models for the quality and fairness of the results. This is one area that needs a lot of improvement."

"The solution's user experience is an area that has room for improvement."

More IBM Cloud Pak for Data cons

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

"As far as I remember, not all connectors worked very well. They can add more connectors and more drivers to the process to integrate with more flows."

"Although it is a low-code solution with a graphical interface, often the error messages that you get are of the type that a developer would be happy with. You get a big stack of red text and Java errors displayed on the screen, and less technical people can get intimidated by that. It can be a bit intimidating to get a wall of red error messages displayed. Other graphical tools that are focused at the power user level provide a much more user-friendly experience in dealing with your exceptions and guiding the user into where they've made the mistake."

"The support for the Enterprise Edition is okay, but what they have done in the last three or four years is move more and more things to that edition. The result is that they are breaking the Community Edition. That's what our impression is."

"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. That is the biggest bug if you are using Git."

"One thing that I don't like, just a little, is the backward compatibility."

"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."

"The reporting definitely needs improvement. There are a lot of general, basic features that it doesn't have. A simple feature you would expect a reporting tool to have is the ability to search the repository for a report. It doesn't even have that capability. That's been a feature that we've been asking for since the beginning and it hasn't been implemented yet."

More Pentaho Data Integration and Analytics cons

Pricing and Cost Advice

"I don't have the exact licensing cost for IBM Cloud Pak for Data, as my company is still finalizing requirements, including monthly, yearly, and three-year licensing fees. Still, on a scale of one to five, I'd rate it a three because, compared to other vendors, it's more complicated."

"For the licensing of the solution, there is a yearly payment that needs to be made. Also, since it is expensive, cost-wise, I rate the solution an eight or nine out of ten."

"The solution is expensive."

"IBM Cloud Pak for Data is expensive. If we include the training time and the machine learning, it's expensive. The cost of the execution is more reasonable."

"Cloud Pak's cost is a little high."

"It's quite expensive."

"The solution's pricing is competitive with that of other vendors."

"I think that this product is too expensive for smaller companies."

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

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

"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."

"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."

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

"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."

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

"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."

More Pentaho Data Integration and Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

27%

Computer Software Company

11%

Manufacturing Company

10%

Government

Financial Services Firm

22%

Computer Software Company

15%

Government

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about IBM Cloud Pak for Data?

DataStage allows me to connect to different data sources.

See all answers

What is your experience regarding pricing and costs for IBM Cloud Pak for Data?

The setup cost is very expensive. The cost depends on the pieces of the solution I'm using, how much data I have, and whether it's on the cloud or on-prem.

See all answers

What needs improvement with IBM Cloud Pak for Data?

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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

IBM InfoSphere DataStage vs IBM Cloud Pak for Data

Compared 41% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs IBM Cloud Pak for Data

Compared 17% of the time

Azure Data Factory vs IBM Cloud Pak for Data

Compared 12% of the time

Denodo vs IBM Cloud Pak for Data

Compared 11% of the time

Palantir Foundry vs IBM Cloud Pak for Data

Compared 7% of the time

More IBM Cloud Pak for Data Competitors

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

Compared 18% of the time

SSIS vs Pentaho Data Integration and Analytics

Compared 13% of the time

Talend Open Studio vs Pentaho Data Integration and Analytics

Compared 11% of the time

Informatica PowerCenter vs Pentaho Data Integration and Analytics

Compared 7% of the time

Azure Data Factory vs Pentaho Data Integration and Analytics

Compared 6% of the time

More Pentaho Data Integration and Analytics Competitors

Product Reports

Buyer's Guide

IBM Cloud Pak for Data

April 2025

Download IBM Cloud Pak for Data product report

Buyer's Guide

Pentaho Data Integration and Analytics

March 2025

Pentaho Data Integration and Analytics report

Download Pentaho Data Integration and Analytics product report

Also Known As

Cloud Pak for Data

Hitachi Lumada Data Integration, Kettle, Pentaho Data Integration

Overview

IBM Cloud Pak® for Data is a fully-integrated data and AI platform that modernizes how businesses collect, organize and analyze data to infuse AI throughout their organizations. Cloud-native by design, the platform unifies market-leading services spanning the entire analytics lifecycle. From data management, DataOps, governance, business analytics and automated AI, IBM Cloud Pak for Data helps eliminate the need for costly, and often competing, point solutions while providing the information architecture you need to implement AI successfully.

Building on the streamlined hybrid-cloud foundation of Red Hat® OpenShift®, IBM Cloud Pak for Data takes advantage of the underlying resource and infrastructure optimization and management. The solution fully supports multicloud environments such as Amazon Web Services (AWS), Azure, Google Cloud, IBM Cloud™ and private cloud deployments. Find out how IBM Cloud Pak for Data can lower your total cost of ownership and accelerate innovation.

IBM

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

Sample Customers

Qatar Development Bank, GuideWell, Skanderborg Music Festival

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

Buyer's Guide

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

April 2025

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

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