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Pentaho Data Integration and Analytics vs Spring Cloud Data Flow comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 2024

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
21st
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
53
Ranking in other categories
No ranking in other categories
Spring Cloud Data Flow
Ranking in Data Integration
22nd
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Streaming Analytics (9th)
 

Mindshare comparison

As of May 2025, in the Data Integration category, the mindshare of Pentaho Data Integration and Analytics is 1.6%, up from 0.6% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.1%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

Ryan Ferdon - PeerSpot reviewer
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 Also, the UI is a bit outdated, but I'm more of a fan of function over how something looks.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.
NitinGoyal - PeerSpot reviewer
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.

Quotes from Members

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

Pros

"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."
"It is easy to use, install, and start working with."
"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."
"The amount of data that it loads and processes is good."
"It's my understanding that the product can scale."
"I absolutely love Hitachi. I'm one of the forefront supporters of Hitachi for my firm. It's so easy to integrate within our environments. In terms of being able to quickly build ETL jobs, transform, and then automate them, it's really easy to integrate throughout for data analytics."
"Flexible deployment, in any environment, is very important to us. That is the key reason why we ended up with these tools. Because we have a very highly secure environment, we must be able to install it in multiple environments on multiple different servers. The fact that we could use the same tool in all our environments, on-prem and in the cloud, was very important to us."
"Data transformation within Pentaho is a nice feature that they have and that I value."
"The most valuable feature is real-time streaming."
"The dashboards in Spring Cloud Dataflow are quite valuable."
"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."
"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 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 best thing I like about Spring Cloud Data Flow is its plug-and-play model."
"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 product is very user-friendly."
 

Cons

"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."
"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."
"The web interface is rusty, and the biggest problem with Pentaho is debugging and troubleshooting. It isn't easy to build the pipeline incrementally. At least in our case, it's hard to find a way to execute step by step in the debugging mode."
"​I work with the Community Edition, therefore I do not have support. There was an issue that I could not resolve with community support.​"
"I have been facing some difficulties when working with large datasets. It seems that when there is a large amount of data, I experience memory errors."
"The performance could be improved. If they could have analytics perform well on large volumes, that would be a big deal for our products."
"I would like to see more improvements with AS400 DB2."
"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."
"I would improve the dashboard features as they are not very user-friendly."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
"The solution's community support could be improved."
"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."
"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."
"Some of the features, like the monitoring tools, are not very mature and are still evolving."
 

Pricing and Cost Advice

"There is a good open source option (Community Edition)​."
"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."
"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."
"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 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."
"For most development tasks, the Enterprise edition should be sufficient. It depends on the type of support that you require for your production environment."
"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."
"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."
"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."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
22%
Computer Software Company
15%
Government
7%
Manufacturing Company
5%
Financial Services Firm
26%
Computer Software Company
18%
Retailer
7%
Manufacturing Company
5%
 

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...
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, ...
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...
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...
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...
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...
 

Also Known As

Hitachi Lumada Data Integration, Kettle, Pentaho Data Integration
No data available
 

Overview

 

Sample Customers

66Controls, Providential Revenue Agency of Ro Negro, NOAA Information Systems, Swiss Real Estate Institute
Information Not Available
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