Azure Data Factory vs Oracle Data Integrator Cloud Service comparison

"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."

"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 two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable."

"Data Factory's most valuable feature is Copy Activity."

"The data copy template is a valuable feature."

"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."

"We have found the bulk load feature very valuable."

"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."

"Oracle integration cloud has got the adapters for all their products, which makes integration faster."

"Having a single vendor supporting the entire suite of applications."

"The solution is easy to manage and offers good integration. You can run all the tasks one by one which is really helpful, and pick the day and time to do so."

"The most valuable thing to me is its simplicity. A person with zero knowledge can also develop the integration without having extensive technology knowledgebase. They can also work on creating their own integration."

"Oracle Data Integrator helps us build tables and data marts and allows us to schedule them daily, for nearly real-time data warehousing."

"The data is stored in the cloud, making it easy to download data simultaneously into multiple smaller servers, effectively downsizing the process."

"It's on the cloud, so it's scalable and quite easy to work with."

"There is no built-in pipeline exit activity when encountering an error."

"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."

"The user interface could use improvement. It's not a major issue but it's something that can be improved."

"It would be better if it had machine learning capabilities."

"They should work on optimizing their licensing model and pricing structure."

"Data Factory could be improved in terms of data transformations by adding more metadata extractions."

"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."

"There aren't many third-party extensions or plugins available in the solution."

"The pricing could be more competitive."

"Bulk uploading can be a problem when you hit the upper limit."

"I would like to see different cloud adapters or connectors in case of integration. When you have Oracle to Oracle, they are good. They have really good connectors, but if it is a different ERP, like Obsidian, that is where they are faced with problems in OIC."

"It's lacking a lot of mapping features that Oracle OSB and SOA have. It needs to evolve a lot."

"I've found technical support not very effective. They should work to improve their services."

"It can be made much easier for users. They should be allowed to easily monitor the data extraction and flow, allowing them to observe real-time data flow within the software, making the process straightforward."

"This is an expensive solution compared to other products on the market."

"Data Factory is affordable."

"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."

"The licensing cost is included in the Synapse."

"Our licensing fees are approximately 15,000 ($150 USD) per month."

"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."

"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."

"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."

"The price is competitive compared to Boomi which is much higher."