We performed a comparison between Azure Data Factory and Collibra Catalog based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration."From what we have seen so far, the solution seems very stable."
"It is easy to deploy workflows and schedule jobs."
"Allows more data between on-premises and cloud solutions"
"The most valuable feature is the ease in which you can create an ETL pipeline."
"The trigger scheduling options are decently robust."
"I like how you can create your own pipeline in your space and reuse those creations. You can collaborate with other people who want to use your code."
"We use the solution to move data from on-premises to the cloud."
"We have been using drivers to connect to various data sets and consume data."
"We have had no complaints about the stability."
"The data lineage capability is valuable as it shows how different sources are connected and how data flows, which is crucial for projects like migrations. Moreover, data lineage visualization in Collibra Catalog aids our data governance initiatives."
"Collibra Catalog's best feature is the data quality checker."
"Collibra Catalog has significantly enhanced data governance and compliance for our team, primarily through its valuable feature of endpoint lineage enabling visual representation of the data."
"Collibra Catalog is simple to use and user-friendly for those who are not technically inclined since it is easy to find while also easy to see data lineage diagrams."
"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."
"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."
"There should be a way that it can do switches, so if at any point in time I want to do some hybrid mode of making any data collections or ingestions, I can just click on a button."
"Lacks in-built streaming data processing."
"DataStage is easier to learn than Data Factory because it's more visual. Data Factory has some drag-and-drop options, but it's not as intuitive as DataStage. It would be better if they added more drag-and-drop features. You can start using DataStage without knowing the code. You don't need to learn how the code works before using the solution."
"It can improve from the perspective of active logging. It can provide active logging information."
"The support and the documentation can be improved."
"Data Factory could be improved by eliminating the need for a physical data area. We have to extract data using Data Factory, then create a staging database for it with Azure SQL, which is very, very expensive. Another improvement would be lowering the licensing cost."
"I'd like to see more integration with other reporting sources."
"The tool's overall functionalities need to improve since, nowadays, many tools, from a business perspective, are easy to use."
"A key area for improvement in Collibra Catalog lies in its integration capabilities, particularly with a broader range of sources."
"Collibra Catalog could improve its automation to increase the efficiency of the software."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Collibra Catalog is ranked 3rd in Metadata Management with 5 reviews. Azure Data Factory is rated 8.0, while Collibra Catalog is rated 7.8. 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 Collibra Catalog writes "A user-friendly for those who are not technically inclined and useful for cataloging various reports". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Microsoft Azure Synapse Analytics, whereas Collibra Catalog is most compared with Informatica Enterprise Data Catalog, Ab Initio Co>Operating System, Talend Data Management Platform, Palantir Foundry and Talend Open Studio.
We monitor all Data Integration 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.
