We performed a comparison between Azure Data Factory and Matillion ETL 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."
"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"The trigger scheduling options are decently robust."
"I enjoy the ease of use for the backend JSON generator, the deployment solution, and the template management."
"One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect."
"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."
"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."
"Allows more data between on-premises and cloud solutions"
"Matillion ETL helps manage data movement, ingestion, and transformation through pipelines."
"It has improved the costs of managing my customer’s data."
"The product's initial setup phase was easy."
"The technical support treats us well. They already have a support portal, and they are responsive, which helps."
"It has good integrations with Amazon Redshift and other AWS services."
"It can scale to a great extent. It can handle the load that we are putting on it, which is about 5TBs."
"The most valuable feature of Matillion ETL is the UI experience in which you can drag and drop most of the transformation."
"It's been able to do everything we require."
"Lacks in-built streaming data processing."
"I have not found any real shortcomings within the product."
"The performance could be better. It would be better if Azure Data Factory could handle a higher load. I have heard that it can get overloaded, and it can't handle it."
"We have experienced some issues with the integration. This is an area that needs improvement."
"Azure Data Factory can improve by having support in the drivers for change data capture."
"They require more detailed error reporting, data normalization tools, easier connectivity to other services, more data services, and greater compatibility with other commonly used schemas."
"The user interface could use improvement. It's not a major issue but it's something that can be improved."
"Azure Data Factory's pricing in terms of utilization could be improved."
"To complete the pipeline, they might want to include some connectors which would put the data into different platforms. This would be helpful."
"The cost of the solution is high and could be reduced."
"In the next release, we would like to have connections to more databases."
"When using the SQL loader type there were not a lot of pre-processing features for the data. For example, if there is a table with twenty columns, but we only want to load ten columns. In that case, we can use a security script to select the specific columns needed. However, if we want to perform extensive pre-processing of the data, I faced some challenges with Matillion ETL. I did not encounter many challenges, but my overall experience is limited as I only have three years of experience."
"The improvement area could be possible if the tool provides better integration capabilities with other ecosystems, including governance tools or data cataloging tools, as it is currently an area where the solution is lacking."
"Sometimes, we have issues with the solution's stability and need to restart it for three weeks or more."
"Unlike Snowflake which automatically takes care of upgrading to the latest version and includes additional features, with Matillion ETL we need to do this ourselves."
"The product must enhance its near-real-time data capture feature."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Matillion ETL is ranked 4th in Cloud Data Integration with 24 reviews. Azure Data Factory is rated 8.0, while Matillion ETL is rated 8.6. 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 Matillion ETL writes "Efficient data integration and transformation with seamless cloud-native integration". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer and Snowflake, whereas Matillion ETL is most compared with Snowflake, AWS Glue, Informatica PowerCenter, SSIS and Informatica Cloud Data Integration. See our Azure Data Factory vs. Matillion ETL report.
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