We performed a comparison between Azure Data Factory 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."Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."
"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."
"The trigger scheduling options are decently robust."
"We haven't had any issues connecting it to other products."
"The tool's most valuable features are its connectors. It has many out-of-the-box connectors. We use ADF for ETL processes. Our main use case involves integrating data from various databases, processing it, and loading it into the target database. ADF plays a crucial role in orchestrating these ETL workflows."
"I like the basic features like the data-based pipelines."
"It is easy to integrate."
"UI is easy to navigate and I can retrieve VTL code without knowing in-depth coding languages."
"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."
"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."
"Data transformation within Pentaho is a nice feature that they have and that I value."
"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 area where Lumada has helped us is in the commercial area. There are many extractions to compose reports about our sales team performance and production steps. Since we are using Lumada to gather data from each industry in each country. We can get data from Argentina, Chile, Brazil, and Colombia at the same time. We can then concentrate and consolidate it in only one place, like our data warehouse. This improves our production performance and need for information about the industry, production data, and commercial data."
"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."
"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."
"It's my understanding that the product can scale."
"I would like to see this time travel feature in Snowflake added to Azure Data Factory."
"The speed and performance need to be improved."
"For some of the data, there were some issues with data mapping. Some of the error messages were a little bit foggy. There could be more of a quick start guide or some inline examples. The documentation could be better."
"I would like to be informed about the changes ahead of time, so we are aware of what's coming."
"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."
"It can improve from the perspective of active logging. It can provide active logging information."
"Data Factory's performance during heavy data processing isn't great."
"It would be better if it had machine learning capabilities."
"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 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."
"The support for the Enterprise Edition is okay, but what they have done in the last three or four years is move more and more things to that edition. The result is that they are breaking the Community Edition. That's what our impression is."
"I would like to see more improvements with AS400 DB2."
"I was not happy with the Pentaho Report Designer because of the way it was set up. There was a zone and, under it, another zone, and under that another one, and under that another one. There were a lot of levels and places inside the report, and it was a little bit complicated. You have to search all these different places using a mouse, clicking everywhere... each report is coded in a binary file... You cannot search with a text search tool..."
"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."
"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."
"If you develop it on MacBook, it'll be quite a hassle."
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Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Pentaho Data Integration and Analytics is ranked 16th in Data Integration with 48 reviews. Azure Data Factory is rated 8.0, while Pentaho Data Integration and Analytics is rated 8.0. The top reviewer of Azure Data Factory writes "The data factory agent is quite good but pricing needs to be more transparent". 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". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Microsoft Azure Synapse Analytics, whereas Pentaho Data Integration and Analytics is most compared with SSIS, Talend Open Studio, Oracle Data Integrator (ODI), AWS Glue and SAP Data Services. See our Azure Data Factory vs. Pentaho Data Integration and Analytics report.
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