We performed a comparison between Informatica Enterprise Data Catalog and Pentaho Data Integration and Analytics based on real PeerSpot user reviews.
Find out in this report how the two Metadata Management solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The capability of the tool to scan and capture the metadata from a variety of sources is one of the capabilities that I find most useful. The central repository into which it is going to put that captured metadata is the best."
"I like EDC's self-service capabilities. You can put the catalog on the intranet inside the organization, so users can search for something. People in the research world have specialized systems, and you might find data from various places that sound similar."
"The solution scales well."
"The most valuable feature of Informatica Enterprise Data Catalog is it provides clients with a full view of the enterprise data assets. For example, how many data assets they have and who owns them."
"The way that the solution scans is very useful."
"The most valuable feature is its ability to extract metadata from various sources- be it an old SaaS application or the latest cloud application."
"The product seems stable enough."
"The metadata management of Informatica is great."
"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."
"It's very simple compared to other products out there."
"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."
"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."
"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."
"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."
"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."
"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."
"Informatica Enterprise Data Catalog could improve by having a much better user interface. It is not user-friendly."
"It is more complicated to extract data using the product compared to Visio. The system could display the details on the screen."
"IEDC can improve the comparison of lineages."
"The UX and UI of the solution are areas with certain shortcomings where improvements can be made in the future."
"The scalability is tough."
"They have to improve their relationship discovery tool. They say that they have AI inside, but this AI did not automatically find relationships or suggested relationships between entities."
"It is not easy to set up and configure the tool."
"Interoperability is one area where EDC has room for improvement. It was challenging when the faculty took over the data world and had specific vendors they wanted to use, and some were not particularly open platforms."
"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."
"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."
"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."
"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."
"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."
"If you develop it on MacBook, it'll be quite a hassle."
"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."
"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."
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Informatica Enterprise Data Catalog is ranked 1st in Metadata Management with 12 reviews while Pentaho Data Integration and Analytics is ranked 15th in Data Integration with 48 reviews. Informatica Enterprise Data Catalog is rated 7.4, while Pentaho Data Integration and Analytics is rated 8.0. The top reviewer of Informatica Enterprise Data Catalog writes "Great metadata management with more visibility and great technical support". 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". Informatica Enterprise Data Catalog is most compared with Alation Data Catalog, Collibra Catalog, AWS Glue, Informatica PowerCenter and Denodo, whereas Pentaho Data Integration and Analytics is most compared with Azure Data Factory, SSIS, Talend Open Studio, AWS Glue and Oracle Data Integrator (ODI). See our Informatica Enterprise Data Catalog vs. Pentaho Data Integration and Analytics report.
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