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."For developers that are very accustomed to the Microsoft development studio, it's very easy for them to complete end-to-end data integration."
"Most of our customers are Microsoft shops and prefer Azure Data Factory because they have good licensing options and a trust factor with Microsoft."
"The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem."
"The solution can scale very easily."
"The most valuable feature of this solution would be ease of use."
"The solution is okay."
"It is beneficial that the solution is written with Spark as the back end."
"On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good."
"Data transformation within Pentaho is a nice feature that they have and that I value."
"Pentaho Data Integration is quite simple to learn, and there is a lot of information available online."
"We're using the PDI and the repository function, and they give us the ability to easily generate reporting and output, and to access data. We also like the ability to schedule."
"This solution allows us to create pipelines using a minimal amount of custom coding."
"One of the valuable features is the ability to use PL/SQL statements inside the data transformations and jobs."
"Sometimes, it took a whole team about two weeks to get all the data to prepare and present it. After the optimization of the data, it took about one to two hours to do the whole process. Therefore, it has helped a lot when you talk about money, because it doesn't take a whole team to do it, just one person to do one project at a time and run it when you want to run it. So, it has helped a lot on that side."
"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."
"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."
"I would like to be informed about the changes ahead of time, so we are aware of what's coming."
"It can improve from the perspective of active logging. It can provide active logging information."
"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."
"Data Factory could be improved in terms of data transformations by adding more metadata extractions."
"My only problem is the seamless connectivity with various other databases, for example, SAP."
"The one element of the solution that we have used and could be improved is the user interface."
"Azure Data Factory's pricing in terms of utilization could be improved."
"The number of standard adaptors could be extended further."
"If you develop it on MacBook, it'll be quite a hassle."
"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."
"I could not connect to our Hadoop environment in an easy and flexible way, and it was important to scale our data warehouse."
"I work with the Community Edition, therefore I do not have support. There was an issue that I could not resolve with community support."
"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."
"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."
"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 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 →
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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