We performed a comparison between Azure Data Factory and Oracle Exadata 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."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."
"An excellent tool for pipeline orchestration."
"The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem."
"From what we have seen so far, the solution seems very stable."
"The security of the agent that is installed on-premises is very good."
"I like that it's a monolithic data platform. This is why we propose these solutions."
"Allows more data between on-premises and cloud solutions"
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."
"The offloading of data to the SIM is a valuable feature."
"It is the best solution for OLTP and data warehousing."
"The performance on the databases is good."
"The most valuable feature of Oracle Exadata is the storage available."
"Oracle Exadata is stable."
"The product is flexible."
"The most valuable feature of Oracle Exadata is its capabilities for storing and processing data. It is very good for our domain."
"The tool's performance is good."
"When the record fails, it's tough to identify and log."
"Lacks in-built streaming data processing."
"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."
"The solution needs to integrate more with other providers and should have a closer integration with Oracle BI."
"There are limitations when processing more than one GD file."
"In the next release, it's important that some sort of scheduler for running tasks is added."
"We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on."
"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."
"Oracle Exadata has room for improvement in pricing, especially for smaller companies. The solution is okay for bigger companies, but for smaller companies, it isn't."
"The solution's pricing is very high."
"The scalability can be improved as it is not a parallel execution."
"The initial setup process is very difficult and extremely complex."
"There's room for improvement in terms of deployment, as it could be made faster and more user-friendly."
"Oracle Exadata could improve the platform performance tuning should be easier, automated, and user-friendly."
"Since the product is an appliance, it is very costly."
"The customization can sometimes be difficult to achieve."
Azure Data Factory is ranked 3rd in Cloud Data Warehouse with 81 reviews while Oracle Exadata is ranked 2nd in Data Warehouse with 125 reviews. Azure Data Factory is rated 8.0, while Oracle Exadata is rated 8.4. 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 Exadata writes "Offers a variety of valuable features". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and IBM InfoSphere DataStage, whereas Oracle Exadata is most compared with Oracle Database Appliance, Teradata, Oracle Autonomous Data Warehouse, Snowflake and Amazon Redshift. See our Azure Data Factory vs. Oracle Exadata report.
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We monitor all Cloud Data Warehouse 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.
