Microsoft's Azure Data Factory is a service built for all data integration needs and skill levels. It is designed to allow the user to easily construct ETL and ELT processes code-free within the intuitive visual environment, or write one's own code. Visually integrate data sources using more than 80 natively built and maintenance-free connectors at no added cost. Focus on data—the serverless integration service does the rest.
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Oracle Integration (OIC)
Score 7.9 out of 10
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The Oracle Integration Cloud Service is an iPaaS providing prebuilt integration flows between applications, including other Oracle products. The Integration Cloud Service is scaled for enterprises, with prebuilt codeless adapters for on-premises and SaaS systems and low-code automation capabilities.
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Pricing
Azure Data Factory
Oracle Integration (OIC)
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure Data Factory
Oracle Integration (OIC)
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
Optional
Additional Details
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More Pricing Information
Community Pulse
Azure Data Factory
Oracle Integration (OIC)
Features
Azure Data Factory
Oracle Integration (OIC)
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Azure Data Factory
8.5
10 Ratings
3% above category average
Oracle Integration (OIC)
-
Ratings
Connect to traditional data sources
9.010 Ratings
00 Ratings
Connecto to Big Data and NoSQL
8.010 Ratings
00 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Azure Data Factory
7.8
10 Ratings
3% below category average
Oracle Integration (OIC)
-
Ratings
Simple transformations
8.710 Ratings
00 Ratings
Complex transformations
7.010 Ratings
00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Azure Data Factory
6.3
10 Ratings
21% below category average
Oracle Integration (OIC)
-
Ratings
Data model creation
4.57 Ratings
00 Ratings
Metadata management
5.58 Ratings
00 Ratings
Business rules and workflow
6.010 Ratings
00 Ratings
Collaboration
7.09 Ratings
00 Ratings
Testing and debugging
6.310 Ratings
00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Azure Data Factory
5.7
10 Ratings
33% below category average
Oracle Integration (OIC)
-
Ratings
Integration with data quality tools
4.310 Ratings
00 Ratings
Integration with MDM tools
7.09 Ratings
00 Ratings
Cloud Data Integration
Comparison of Cloud Data Integration features of Product A and Product B
Best scenario is for ETL process. The flexibility and connectivity is outstanding. For our environment, SAP data connectivity with Azure Data Factory offers very limited features compared to SAP Data Sphere. Due to the limited modelling capacity of the tool, we use Databricks for data modelling and cleaning. Usage of multiple tools could have been avoided if adf has modelling capabilities.
Oracle Process Cloud is suited for medium-sized companies and up who want to create applications that can automate tasks without the need of recruiting more software developers. With a couple hours of training, any member of the organization's business team will be well-equipped with all of the knowledge that is needed to use Oracle Process Cloud effectively. If your IT team is large and able to take upon the task of making the given application, then something like Oracle BPM is a better solution.
New enhanced activities that are targeted to reduce the integration pain. For example, file stage activity reduces the pain of chunking the input file while sending and mapping the data to the target application. Stage activity takes care of it automatically for the customer. Similarly, recommendation on the mapper is a huge plus for people looking for common integration.
There are around 50 adapters available including dedicated out of the box application adapters and generic technologies adapters on OICS. The best part of these application adapters is that they are designed considering LOB users. Most of the time integration implementor does not require, application knowledge to perform the integration. OICS has some of Oracle Cloud applications adapters which make integration much easier may not be available in other integration platforms.
Inbuilt diagnostic dashboard and error hospital makes this product lucrative. OICS also comes with integrated Process Cloud and Visual Builder at the same cost. the customer can have seamless integration with Apiary and SSI on demand.
Granularity of Errors: Sometimes, Azure Data Factory provides error messages that are too generic or vague for us, making it challenging to pinpoint the exact cause of a pipeline failure. Enhanced error messages with more actionable details would greatly assist us as users in debugging their pipelines.
Pipeline Design UI: In my experience, the visual interface for designing pipelines, especially when dealing with complex workflows or numerous activities, can become cluttered. I think a more intuitive and scalable design interface would improve usability. In my opinion, features like zoom, better alignment tools, or grouping capabilities could make managing intricate designs more manageable.
Native Support: While Azure Data Factory does support incremental data loads, in my experience, the setup can be somewhat manual and complex. I think native and more straightforward support for Change Data Capture, especially from popular databases, would simplify the process of capturing and processing only the changed data, making regular data updates more efficient
Currently, it is not retaining the logs for more than 3 days, which it needs to address.
We also need some functionality inside the interface to re-push the same transaction again so that it will be helpful while testing and fixing the issue.
Also, some log errors are not giving the correct details. Oracle needs to rectify those.
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.
We have not had need to engage with Microsoft much on Azure Data Factory, but they have been responsive and helpful when needed. This being said, we have not had a major emergency or outage requiring their intervention. The score of seven is a representation that they have done well for now, but have not proved out their support for a significant issue
Azure Data Factory helps us automate to schedule jobs as per customer demands to make ETL triggers when the need arises. Anyone can define the workflow with the Azure Data Factory UI designer tool and easily test the systems. It helped us automate the same workflow with programming languages like Python or automation tools like ansible. Numerous options for connectivity be it a database or storage account helps us move data transfer to the cloud or on-premise systems.
The nearest thing I have used to OIC is UiPath, as it is often used as a tool to integrate software together. However, it is much more suited to legacy software which have little to no API endpoints. If the infrastructure already exists I understand why people use RPA for integration, however for when API's are easily accessible and you're using Oracle tools, OIC is better.
The modern and advanced analytical abilities in Oracle Process Cloud are also a missing element that should be catered to.
This tool is used greatly for IT departments at a lower level with some very basic and limited access for general employees only.
Oracle Process Cloud has many advantages like it offers some very great and scalable solutions.
I find Oracle Process Cloud pretty straightforward and easy as compared to the different options available. Lastly, I think that as it is just one platform, managing the Oracle Process Cloud is pretty easy too.
