Try our new research platform with insights from 80,000+ expert users

Pentaho Data Integration and Analytics vs StreamSets comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Pentaho Data Integration an...
Ranking in Data Integration
30th
Average Rating
8.0
Reviews Sentiment
5.8
Number of Reviews
51
Ranking in other categories
No ranking in other categories
StreamSets
Ranking in Data Integration
9th
Average Rating
8.4
Reviews Sentiment
7.5
Number of Reviews
24
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of November 2024, in the Data Integration category, the mindshare of Pentaho Data Integration and Analytics is 1.4%, up from 0.5% compared to the previous year. The mindshare of StreamSets is 1.7%, up from 1.3% 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 Also, the UI is a bit outdated, but I'm more of a fan of function over how something looks.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.
Reyansh Kumar - PeerSpot reviewer
We no longer need to hire highly skilled data engineers to create and monitor data pipelines
The things I like about StreamSets are its * overall user interface * efficiency * product features, which are all good. Also, the scheduling within the data engineering pipeline is very much appreciated, and it has a wide range of connectors for connecting to any data sources like SQL Server, AWS, Azure, etc. We have used it with Kafka, Hadoop, and Azure Data Factory Datasets. Connecting to these systems with StreamSets is very easy. You just need to configure the data sources, the paths and their configurations, and you are ready to go. It is very efficient and very easy to use for ETL pipelines. It is a GUI-based interface in which you can easily create or design your own data pipelines with just a few clicks. As for moving data into modern analytics systems, we are using it with Microsoft Power BI, AWS, and some on-premises solutions, and it is very easy to get data from StreamSets into them. No hardcore coding or special technical expertise is required. It is also a no-code platform in which you can configure your data sources and data output for easy configuration of your data pipeline. This is a very important aspect because if a tool requires code development, we need to hire software developers to get the task done. By using StreamSets, it can be done with a few clicks.

Quotes from Members

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

Pros

"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."
"We also haven't had to create any custom Java code. Almost everywhere it's SQL, so it's done in the pipeline and the configuration. That means you can offload the work to people who, while they are not less experienced, are less technical when it comes to logic."
"Pentaho Data Integration is quite simple to learn, and there is a lot of information available online."
"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."
"Lumada has allowed us to interact with our employees more effectively and compensate them properly. One of the cool things is that we use it to generate commissions for our salespeople and bonuses for our warehouse people. It allows us to get information out to them in a timely fashion. We can also see where they're at and how they're doing."
"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."
"This solution allows us to create pipelines using a minimal amount of custom coding."
"Sometimes, it took a whole team about two weeks to get all the data to prepare and present it. After the optimization of the data, it took about one to two hours to do the whole process. Therefore, it has helped a lot when you talk about money, because it doesn't take a whole team to do it, just one person to do one project at a time and run it when you want to run it. So, it has helped a lot on that side."
"The entire user interface is very simple and the simplicity of creating pipelines is something that I like very much about it. The design experience is very smooth."
"The most valuable feature is the pipelines because they enable us to pull in and push out data from different sources and to manipulate and clean things up within them."
"I really appreciate the numerous ready connectors available on both the source and target sides, the support for various media file formats, and the ease of configuring and managing pipelines centrally."
"StreamSets’ data drift resilience has reduced the time it takes us to fix data drift breakages. For example, in our previous Hadoop scenario, when we were creating the Sqoop-based processes to move data from source to destinations, we were getting the job done. That took approximately an hour to an hour and a half when we did it with Hadoop. However, with the StreamSets, since it works on a data collector-based mechanism, it completes the same process in 15 minutes of time. Therefore, it has saved us around 45 minutes per data pipeline or table that we migrate. Thus, it reduced the data transfer, including the drift part, by 45 minutes."
"For me, the most valuable features in StreamSets have to be the Data Collector and Control Hub, but especially the Data Collector. That feature is very elegant and seamlessly works with numerous source systems."
"It is really easy to set up and the interface is easy to use."
"The ability to have a good bifurcation rate and fewer mistakes is valuable."
"The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customize it to do what you need. Many other tools have started to use features similar to those introduced by StreamSets, like automated workflows that are easy to set up."
 

Cons

"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."
"I would like to see more improvements with AS400 DB2."
"One thing that I don't like, just a little, is the backward compatibility."
"​There is not a data quality or MDM solution in the Pentaho DI suite.​"
"Should provide additional control for the data warehouse"
"In the Community edition, it would be nice to have more modules that allow you to code directly within the application. It could have R or Python completely integrated into it, but this could also be because I'm using an older version."
"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."
"​I work with the Community Edition, therefore I do not have support. There was an issue that I could not resolve with community support.​"
"The design experience is the bane of our existence because their documentation is not the best. Even when they update their software, they don't publish the best information on how to update and change your pipeline configuration to make it conform to current best practices. We don't pay for the added support. We use the "freeware version." The user community, as well as the documentation they provide for the standard user, are difficult, at best."
"The execution engine could be improved. When I was at their session, they were using some obscure platform to run. There is a controller, which controls what happens on that, but you should be able to easily do this at any of the cloud services, such as Google Cloud. You shouldn't have any issues in terms of how to run it with their online development platform or design platform, basically their execution engine. There are issues with that."
"Sometimes, it is not clear at first how to set up nodes. A site with an explanation of how each node works would be very helpful."
"There aren't enough hands-on labs, and debugging is also an issue because it takes a lot of time. Logs are not that clear when you are debugging, and you can only select a single source for a pipeline."
"In terms of the product, I don't think there is any room for improvement because it is very good. One small area of improvement that is very much needed is on the knowledge base side. Sometimes, it is not very clear how to set up a certain process or a certain node for a person who's using the platform for the first time."
"The documentation is inadequate and has room for improvement because the technical support does not regularly update their documentation or the knowledge base."
"Sometimes, when we have large amounts of data that is very efficiently stored in Hadoop or Kafka, it is not very efficient to run it through StreamSets, due to the lack of efficiency or the resources that StreamSets is using."
"They need to improve their customer care services. Sometimes it has taken more than 48 hours to resolve an issue. That should be reduced. They are aware of small or generic issues, but not the more technical or deep issues. For those, they require some time, generally 48 to 72 hours to respond. That should be improved."
 

Pricing and Cost Advice

"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."
"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 was a cost analysis done and Pentaho did favorably in terms of cost."
"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 primarily work on the Community Version, which is available to use free of charge."
"For most development tasks, the Enterprise edition should be sufficient. It depends on the type of support that you require for your production environment."
"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."
"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 is too fixed. It should be based on how much data you need to process. Some businesses are not so big that they process a lot of data."
"The overall cost is very flexible so it is not a burden for our organization... However, the cost should be improved. For small and mid-size organizations it might be a challenge."
"It has a CPU core-based licensing, which works for us and is quite good."
"We are running the community version right now, which can be used free of charge."
"StreamSets Data Collector is open source. One can utilize the StreamSets Data Collector, but the Control Hub is the main repository where all the jobs are present. Everything happens in Control Hub."
"It's not expensive because you pay per month, and the tasks you can perform with it are huge. It's reliable and cost-effective."
"I believe the pricing is not equitable."
"StreamSets is an expensive solution."
report
Use our free recommendation engine to learn which Data Integration solutions are best for your needs.
816,406 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
23%
Computer Software Company
14%
Government
7%
Comms Service Provider
5%
Financial Services Firm
17%
Computer Software Company
13%
Manufacturing Company
8%
Insurance Company
6%
 

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 do you like most about StreamSets?
The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customiz...
What needs improvement with StreamSets?
We often faced problems, especially with SAP ERP. We struggled because many columns weren't integers or primary keys, which StreamSets couldn't handle. We had to restructure our data tables, which ...
What is your primary use case for StreamSets?
StreamSets is used for data transformation rather than ETL processes. It focuses on transforming data directly from sources without handling the extraction part of the process. The transformed data...
 

Also Known As

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

Learn More

Video not available
 

Overview

 

Sample Customers

66Controls, Providential Revenue Agency of Ro Negro, NOAA Information Systems, Swiss Real Estate Institute
Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge
Find out what your peers are saying about Pentaho Data Integration and Analytics vs. StreamSets and other solutions. Updated: November 2024.
816,406 professionals have used our research since 2012.