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 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."
"It can automatically connect or associate business terms with various options, providing flexibility beyond general capabilities."
"The most valuable feature is its ability to extract metadata from various sources- be it an old SaaS application or the latest cloud application."
"We can scan anything."
"Multifeatured and easily scalable data catalog, with good data domain discovery and data profiling features."
"The way that the solution scans is very useful."
"The solution scales well."
"The metadata management of Informatica is great."
"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."
"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."
"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."
"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 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."
"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."
"It has improved our data integration capabilities."
"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 UX and UI of the solution are areas with certain shortcomings where improvements can be made in the future."
"Currently, there are limitations in processing and the interface."
"This solution is hard to set up and its interface is not user-friendly. It's also not as stable, and the technical support takes a lot of time to solve simple problems."
"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."
"The model is somewhat flexible. There are certain aspects of the model that are not as flexible as we would like. It doesn't do certain things to a great level of depth. So, in situations where we want to drill in to do something specific, we have to essentially copy that data into our own structures in order to add that additional layer of flexibility."
"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."
"It is not easy to set up and configure the tool."
"The scalability is tough."
"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 could not connect to our Hadoop environment in an easy and flexible way, and it was important to scale our data warehouse."
"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."
"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."
"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."
"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."
"Parallel execution could be better in Pentaho. It's very simple but I don't think it works well."
"I work with the Community Edition, therefore I do not have support. There was an issue that I could not resolve with community support."
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Informatica Enterprise Data Catalog is ranked 1st in Metadata Management with 13 reviews while Pentaho Data Integration and Analytics is ranked 16th in Data Integration with 48 reviews. Informatica Enterprise Data Catalog is rated 7.6, 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, Oracle Data Integrator (ODI) and AWS Glue. See our Informatica Enterprise Data Catalog vs. Pentaho Data Integration and Analytics report.
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