We performed a comparison between Azure Data Factory and Informatica Enterprise Data Lake based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration."The solution has a good interface and the integration with GitHub is very useful."
"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"The flexibility that Azure Data Factory offers is great."
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."
"I think it makes it very easy to understand what data flow is and so on. You can leverage the user interface to do the different data flows, and it's great. I like it a lot."
"The initial setup is very quick and easy."
"The most valuable aspect is the copy capability."
"ADF is another ETL tool similar to Informatica that can transform data or copy it from on-prem to the cloud or vice versa. Once we have the data, we can apply various transformations to it and schedule our pipeline according to our business needs. ADF integrates with Databricks. We can call our Databricks notebooks and schedule them via ADF."
"The process of using the tool's scalability option is well documented."
"My only problem is the seamless connectivity with various other databases, for example, SAP."
"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."
"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."
"Areas for improvement in Azure Data Factory include connectivity and integration. When you use integration runtime, whenever there's a failure, the backup process in Azure Data Factory takes time, so this is another area for improvement."
"On the UI side, they could make it a little more intuitive in terms of how to add the radius components. Somebody who has been working with tools like Informatica or DataStage gets very used to how the UI looks and feels."
"The initial setup is not very straightforward."
"The setup and configuration process could be simplified."
"Data Factory could be improved in terms of data transformations by adding more metadata extractions."
"Informatica Enterprise Data Lake's setup process was complex since it doesn't support a lot of real-time systems."
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Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Informatica Enterprise Data Lake is ranked 41st in Data Integration with 1 review. Azure Data Factory is rated 8.0, while Informatica Enterprise Data Lake is rated 7.0. 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 Informatica Enterprise Data Lake writes "A scalable tool that needs a lot of maintenance due to its unstable nature". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Microsoft Azure Synapse Analytics, whereas Informatica Enterprise Data Lake is most compared with Palantir Foundry.
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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.
