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."The Hierarchical Data Stage is good."
"The most valuable feature is the data integration for data warehousing."
"It works with multiple servers and offers high availability."
"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."
"The solution's scalability is really good...we are using multi-instance jobs where you can scale them easily."
"Offers great flexibility."
"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."
"We like the flexibility of modeling."
"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."
"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."
"This solution allows us to create pipelines using a minimal amount of custom coding."
"The solution offers features for data integration and migration. Pentaho Data Integration and Analytics allows the integration of multiple data sources into one. The product is user-friendly and intuitive to use for almost any business."
"I can create faster instructions than writing with SQL or code. Also, I am able to do some background control of the data process with this tool. Therefore, I use it as an ELT tool. I have a station area where I can work with all the information that I have in my production databases, then I can work with the data that I created."
"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."
"The amount of data that it loads and processes is good."
"One of the most valuable features is the ability to create many API integrations. I'm always working with advertising agents and using Facebook and Instagram to do campaigns. We use Pentaho to get the results from these campaigns and to create dashboards to analyze the results."
"The response time from support is slow and needs to be improved."
"The solution should be more user-friendly."
"It would be great if they can include some basic version of data quality checking features."
"The interface needs improvement. It is really too technical. That is the main problem."
"The graphical user interface (GUI) feels a lot like the interfaces from the 1980s."
"I'd like to be able to do more with the data and metadata, including copy and pasting, et cetera."
"There could be more customization options for the product."
"Their web interface is good but the on-prem sites are outdated. The solution could also be improved if they could integrate the data pipeline scheduling part of their interface."
"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."
"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."
"The product needs more plugins."
"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."
"Parallel execution could be better in Pentaho. It's very simple but I don't think it works well."
"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 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."
"I work with different databases. I would like to work with more connectors to new databases, e.g., DynamoDB and MariaDB, and new cloud solutions, e.g., AWS, Azure, and GCP. If they had these connectors, that would be great. They could improve by building new connectors. If you have native connections to different databases, then you can make instructions more efficient and in a more natural way. You don't have to write any scripts to use that connector."
More Pentaho Data Integration and Analytics Pricing and Cost Advice →
IBM InfoSphere DataStage is ranked 7th in Data Integration with 37 reviews while Pentaho Data Integration and Analytics is ranked 22nd in Data Integration with 49 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 SSIS, Azure Data Factory, Oracle Data Integrator (ODI), Talend Open Studio and AWS Database Migration Service. See our IBM InfoSphere DataStage vs. Pentaho Data Integration and Analytics report.
See our list of best Data Integration vendors.
We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
