We performed a comparison between Pentaho Data Integration and Analytics and StreamSets based on real PeerSpot user reviews.
Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."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."
"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."
"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."
"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."
"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."
"One of the valuable features is the ability to use PL/SQL statements inside the data transformations and jobs."
"We can schedule job execution in the BA Server, which is the front-end product we're using right now. That scheduling interface is nice."
"It makes it pretty simple to do some fairly complicated things. Both I and some of our other BI developers have made stabs at using, for example, SQL Server Integration Services, and we found them a little bit frustrating compared to Data Integration. So, its ease of use is right up there."
"What I love the most is that StreamSets is very light. It's a containerized application. It's easy to use with Docker. If you are a large organization, it's very easy to use Kubernetes."
"Also, the intuitive canvas for designing all the streams in the pipeline, along with the simplicity of the entire product are very big pluses for me. The software is very simple and straightforward. That is something that is needed right now."
"The most valuable would be the GUI platform that I saw. I first saw it at a special session that StreamSets provided towards the end of the summer. I saw the way you set it up and how you have different processes going on with your data. The design experience seemed to be pretty straightforward to me in terms of how you drag and drop these nodes and connect them with arrows."
"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."
"It is a very powerful, modern data analytics solution, in which you can integrate a large volume of data from different sources. It integrates all of the data and you can design, create, and monitor pipelines according to your requirements. It is an all-in-one day data ops solution."
"The UI is user-friendly, it doesn't require any technical know-how and we can navigate to social media or use it more easily."
"StreamSets Transformer is a good feature because it helps you when you are developing applications and when you don't want to write a lot of code. That is the best feature overall."
"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."
"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."
"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."
"The product needs more plugins."
"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'm still in the very recent stage concerning Pentaho Data Integration, but it can't really handle what I describe as "extreme data processing" i.e. when there is a huge amount of data to process. That is one area where Pentaho is still lacking."
"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."
"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."
"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."
"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."
"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."
"Currently, we can only use the query to read data from SAP HANA. What we would like to see, as soon as possible, is the ability to read from multiple tables from SAP HANA. That would be a really good thing that we could use immediately. For example, if you have 100 tables in SQL Server or Oracle, then you could just point it to the schema or the 100 tables and ingestion information. However, you can't do that in SAP HANA since StreamSets currently is lacking in this. They do not have a multi-table feature for SAP HANA. Therefore, a multi-table origin for SAP HANA would be helpful."
"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."
"StreamSets should provide a mechanism to be able to perform data quality assessment when the data is being moved from one source to the target."
"If you use JDBC Lookup, for example, it generally takes a long time to process data."
"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."
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Pentaho Data Integration and Analytics is ranked 15th in Data Integration with 48 reviews while StreamSets is ranked 8th in Data Integration with 24 reviews. Pentaho Data Integration and Analytics is rated 8.0, while StreamSets is rated 8.4. The top reviewer of Pentaho Data Integration and Analytics writes "It's flexible and can do almost anything I want it to do". On the other hand, the top reviewer of StreamSets writes "We no longer need to hire highly skilled data engineers to create and monitor data pipelines". Pentaho Data Integration and Analytics is most compared with SSIS, Azure Data Factory, Talend Open Studio, Oracle Data Integrator (ODI) and AWS Glue, whereas StreamSets is most compared with Fivetran, Azure Data Factory, Informatica PowerCenter, SSIS and IBM InfoSphere DataStage. See our Pentaho Data Integration and Analytics vs. StreamSets report.
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