We performed a comparison between Hitachi Lumada Data Integration and IBM InfoSphere DataStage based on real PeerSpot user reviews.
Find out in this report how the two Data Integration Tools solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
"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 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."
"I can use Python, which is open-source, and I can run other scripts, including Linux scripts. It's user-friendly for running any object-based language. That's a very important feature because we live in a world of open-source."
"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."
"One of the valuable features is the ability to use PL/SQL statements inside the data transformations and jobs."
"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."
"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 fact that it's a low-code solution is valuable. It's good for more junior people who may not be as experienced with programming."
"It is quite useful and powerful."
"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's a robust solution."
"Offers great flexibility."
"When we have needed help from the IBM team, they were helpful. Our company is a premium partner so we get fast responses."
"It works with multiple servers and offers high availability."
"The most valuable feature of the solution is the ability to incorporate very complex business rules in Data Stage."
"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."
"It could be better integrated with programming languages, like Python and R. Right now, if I want to run a Python code on one of my ETLs, it is a bit difficult to do. It would be great if we have some modules where we could code directly in a Python language. We don't really have a way to run Python code natively."
"If you develop it on MacBook, it'll be quite a hassle."
"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."
"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."
"Its basic functionality doesn't need a whole lot of change. There could be some improvement in the consistency of the behavior of different transformation steps. The software did start as open-source and a lot of the fundamental, everyday transformation steps that you use when building ETL jobs were developed by different people. It is not a seamless paradigm. A table input step has a different way of thinking than a data merge step."
"Some of the scheduling features about Lumada drive me buggy. The one issue that always drives me up the wall is when Daylight Savings Time changes. It doesn't take that into account elegantly. Every time it changes, I have to do something. It's not a big deal, but it's annoying."
"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."
"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 initial setup could be more straightforward."
"The solution can be a bit more user-friendly, similar to Informatica."
"It would be useful to provide support for Python, AR, and Java."
"The error messaging needs to be improved."
"Its documentation is not up to the mark. While building APIs, we had a lot of problems trying to get around it because it is not very user-friendly. We tried to get hold of API documentation, but the documentation is not very well thought out. It should be more structured and elaborate. In terms of additional features, I would like to see good reporting on performance and performance-tuning recommendations that can be based on AI. I would also like to see better data profiling information being reported on InfoSphere."
"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."
"Currently lacking virtualization ability."
"In the future, I would like to see more integration with cloud technologies."
More Hitachi Lumada Data Integration Pricing and Cost Advice →
Hitachi Lumada Data Integration is ranked 6th in Data Integration Tools with 24 reviews while IBM InfoSphere DataStage is ranked 11th in Data Integration Tools with 10 reviews. Hitachi Lumada Data Integration is rated 7.8, while IBM InfoSphere DataStage is rated 7.8. The top reviewer of Hitachi Lumada Data Integration writes "Saves time and makes it easy for our mixed-skilled team to support the product, but more guidance and better error messages are required in the UI". On the other hand, the top reviewer of IBM InfoSphere DataStage writes "Robust, easy to use, has a simple error logging mechanism, and works very well for huge volumes of data". Hitachi Lumada Data Integration is most compared with SSIS, Talend Open Studio, Informatica Enterprise Data Catalog, Azure Data Factory and Mule Anypoint Platform, whereas IBM InfoSphere DataStage is most compared with SSIS, Talend Open Studio, Azure Data Factory, AWS Glue and Informatica PowerCenter. See our Hitachi Lumada Data Integration vs. IBM InfoSphere DataStage report.
See our list of best Data Integration Tools vendors and best Cloud Data Integration vendors.
We monitor all Data Integration Tools 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.
