We performed a comparison between IBM InfoSphere DataStage and Pentaho Data Integration and Analytics 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."As a data integration platform, it is easy to use. It is quite robust and useful for volumetric analysis when you have huge volumes of data. We have tested it for up to ten million rows, and it is robust enough to process ten million rows internally with its parallel processing. Its error logging mechanism is far simpler and easier to understand than other data integration tools. The newer version of InfoSphere has the data catalog and IDC lineage. They are helpful in the easy traceability of columns and tables."
"The best feature of IBM InfoSphere DataStage for me was that it was very much user-friendly. The solution didn't require that much raw coding because most of its features were drag and drop, plus it had a large number of functionalities."
"It works with multiple servers and offers high availability."
"In IBM DataStage, the Transformer is the most valuable feature for me. It enables me to apply complex transformations, generate the gateway key, and map source tables into the session table."
"The performance optimization is quite good in DataStage. It provides parallelism and pipelining mechanisms"
"The most valuable feature of the solution is the ability to incorporate very complex business rules in Data Stage."
"The Hierarchical Data Stage is good."
"We like the flexibility of modeling."
"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."
"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."
"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."
"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."
"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."
"Provides a good open source option."
"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."
"We would be happy to see in next versions the ability to return several parameters from jobs. Now, jobs can return just one parameter. If they could return several parameters, that would be great."
"It takes a lot of time to actually trigger your job and then go into the logs and other stuff. So all of this is really time-consuming."
"So, there are some features that are missing. If I compare DataStage to Talend, Talend allows you to write custom code in Java or use these tools in your applications as well if you are building a job application. But in DataStage, it does not allow you to write custom code for any component."
"The troubleshooting guide is very bad."
"The pricing should be lower."
"Working with some of the big data components is good, but I can see improvements are needed."
"I'd like to be able to do more with the data and metadata, including copy and pasting, et cetera."
"It would be great if they can include some basic version of data quality checking features."
"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."
"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."
"One thing that I don't like, just a little, is the backward compatibility."
"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."
"The testing and quality could really improve. Every time that there is a major release, we are very nervous about what is going to get broken. We have had a lot of experience with that, as even the latest one was broken. Some basic things get broken. That doesn't look good for Hitachi at all. If there is one place I would advise them to spend some money and do some effort, it is with the quality. It is not that hard to start putting in some unit tests so basic things don't get broken when they do a new release. That just looks horrible, especially for an organization like Hitachi."
"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."
"In terms of the flexibility to deploy in any environment, such as on-premise or in the cloud, we can do the cloud deployment only through virtual machines. We might also be able to work on different environments through Docker or Kubernetes, but we don't have an Azure app or an AWS app for easy deployment to the cloud. We can only do it through virtual machines, which is a problem, but we can manage it. We also work with Databricks because it works with Spark. We can work with clustered servers, and we can easily do the deployment in the cloud. With a right-click, we can deploy Databricks through the app on AWS or Azure cloud."
"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."
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IBM InfoSphere DataStage is ranked 7th in Data Integration with 37 reviews while Pentaho Data Integration and Analytics is ranked 16th in Data Integration with 48 reviews. IBM InfoSphere DataStage is rated 7.8, while Pentaho Data Integration and Analytics is rated 8.0. The top reviewer of IBM InfoSphere DataStage writes "User-friendly with a lot of functions for transmission rules, but has slow performance and not suitable for a huge volume of data". On the other hand, the top reviewer of Pentaho Data Integration and Analytics writes "It's flexible and can do almost anything I want it to do". IBM InfoSphere DataStage is most compared with SSIS, IBM Cloud Pak for Data, Azure Data Factory, Talend Open Studio and Informatica PowerCenter, whereas Pentaho Data Integration and Analytics is most compared with Azure Data Factory, SSIS, Talend Open Studio, Oracle Data Integrator (ODI) and AWS Database Migration Service. See our IBM InfoSphere DataStage vs. Pentaho Data Integration and Analytics report.
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