Overall helpful product that works as advertised.
August 18, 2025

Overall helpful product that works as advertised.

Anonymous | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with Azure Data Factory

Using SHIR to pull records from on-premise databases and storing in ADLS storage. From ADLS storage, bringing data into databricks for analytics use. Roughly 50 different pipelines in each environment, with 3 separate environments. Code is stored and deployed from Azure Dev ops. Alerting is handled via LogicMonitor and Azure Functions.

Pros

  • Step by step processes.
  • Storing infrastructure as code.
  • Alerting on job failures.
  • SHIR

Cons

  • Learning curve for pipeline creation interface.
  • Alerting isn't necessarily built in. Had to work around this to meet team needs.
  • With GIT enabled, some features can only be done via git, while some need to be done via the portal.
  • Still working on ROI. Development is ongoing after some non-Azure Data Factory related changes.
So far product has performed as expected. We were noticing some performance issues, but they were largely Synapse related. This has led to a shift from Synapse to Databricks. Overall this has delayed our analytic platform. Once databricks becomes fully operational, Azure Data Factory will be critical to our environment and future success.

Do you think Azure Data Factory delivers good value for the price?

Yes

Are you happy with Azure Data Factory's feature set?

Yes

Did Azure Data Factory live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Azure Data Factory go as expected?

Yes

Would you buy Azure Data Factory again?

Yes

Pulling data from Databases in a scheduled and controlled pattern. We heavily use the self hosted SHIR option to pull from existing sources. In addition, we have several API's directly from Azure Data Factory using keyvault for passphrase storage. Utilizing GIT in Devops helps promote changes within our multiple environments in a timely matter.

Azure Data Factory Feature Ratings

8.0
Connect to traditional data sources
9
Connecto to Big Data and NoSQL
7
8.0
Simple transformations
9
Complex transformations
7
7.0
Data model creation
7
Metadata management
7
Business rules and workflow
7
Collaboration
8
Testing and debugging
6
6.0
Integration with data quality tools
6

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