We performed a comparison between Azure Data Factory and Oracle Autonomous Data Warehouse based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse 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."
"It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory."
"The trigger scheduling options are decently robust."
"From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connects and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature."
"The solution has a good interface and the integration with GitHub is very useful."
"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."
"I like the basic features like the data-based pipelines."
"We haven't had any issues connecting it to other products."
"Self-patching and runs machine-learning across its logs all the time"
"One advantage is that if you already have an Oracle Database, it easily integrates with that."
"It provides Transparent Data Encryption (TDE) capabilities by default to address data security issues."
"The product is easy to use."
"The performance and scalability are awesome."
"With Oracle Autonomous Data Warehouse, things are much simpler. Creating a structure, initializing the servers, extending the servers, those are all things that are very, very easy. That's the main reason we use it."
"It is an extremely scalable solution since you can dynamically change the resources as some other cloud solutions."
"The solution is self-securing. All data is encrypted and security updates and patches are applied automatically both periodically and off-cycle."
"I would like to be informed about the changes ahead of time, so we are aware of what's coming."
"The initial setup is not very straightforward."
"I have not found any real shortcomings within the product."
"The solution can be improved by decreasing the warmup time which currently can take up to five minutes."
"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."
"When the record fails, it's tough to identify and log."
"User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."
"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."
"Sometimes the solution works differently between the cloud and on-premises. It needs to be more consistent and predictable."
"One of the major problem is creating custom tablespace. The ADB serverless option doesn't support custom tablespace creation, which could cause issues during on-premise database migration that requires specifically named tablespace. There should be an option to create customized tablespace."
"My main suggestion for Oracle is the configuration and key values that come for JSON files. When we create a table, especially if you see in our RedShift or some other stuff, if I create a table on top of a JSON file with multiple array columns or superset columns, those column values create some difficulty in Oracle."
"I would like to see Application Express and Oracle R Enterprise fully supported, and I would like to see Oracle Data Mining supported as a front end."
"The solution could be improved by allowing for migration tools from other cloud services, including migration from Amazon Redshift, RDS, and Aurora."
"The solution lacks visibility options."
"They should make the solution more user-friendly."
"There is a need for more storage to be allocated, but over a period of time, it becomes impossible to reduce it after using it."
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Azure Data Factory is ranked 3rd in Cloud Data Warehouse with 79 reviews while Oracle Autonomous Data Warehouse is ranked 10th in Cloud Data Warehouse with 16 reviews. Azure Data Factory is rated 8.0, while Oracle Autonomous Data Warehouse 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 Oracle Autonomous Data Warehouse writes "A tool for data warehousing that offers scalability, stability, and ease of setup". Azure Data Factory is most compared with Informatica PowerCenter, Alteryx Designer, Informatica Cloud Data Integration, Snowflake and Microsoft Azure Synapse Analytics, whereas Oracle Autonomous Data Warehouse is most compared with Oracle Exadata, Snowflake, Microsoft Azure Synapse Analytics, BigQuery and Vertica. See our Azure Data Factory vs. Oracle Autonomous Data Warehouse report.
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