We performed a comparison between Azure Data Factory and Oracle Data Integrator ODI based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: The main difference between the two products is that Azure Data Factory needs better integration capabilities while users of Oracle Data Integrator (ODI) find that the solution integrates well with other systems.
"Allows more data between on-premises and cloud solutions"
"The solution is okay."
"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 tool's most valuable features are its connectors. It has many out-of-the-box connectors. We use ADF for ETL processes. Our main use case involves integrating data from various databases, processing it, and loading it into the target database. ADF plays a crucial role in orchestrating these ETL workflows."
"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."
"It is a complete ETL Solution."
"For developers that are very accustomed to the Microsoft development studio, it's very easy for them to complete end-to-end data integration."
"Data Factory's best features are simplicity and flexibility."
"Easy to understand, very developer-friendly, and has a big forum community and lots of documentation for support."
"The most valuable features of ODI are the ease of development, you can have a template, and you can onboard transfer very quickly. There's a lot of knowledge modules available that we can use. If you want to connect, for example, a Sibyl, SQL, Oracle, or different products, we don't have to develop them from scratch. They are available, but if it's not, we can go into the marketplace and see if there's a connector there. Having the connector available reduces the amount of hard work needed. We only have to put the inputs and outputs. In some of the products, we use there is already integration available for ODI, which is helpful."
"The most valuable features of ODI are the knowledge modules, such as the Loading Knowledge module and the Check Knowledge module, they are helpful. We can check for the constraints in ODI. That helps in figuring out what are the constraints that are the primary keys created in the tables. We can check them with the Check Knowledge module."
"ODI is a very accessible tool, especially since the mapping functionality has been added."
"Most of the functions are very straightforward, like the data model, mapping, package, and load plan. Thus, a new user could get started very fast."
"Besides loading data, we do most of our transformations in ODI."
"It's scalable."
"ODI's most valuable features are it utilizes the database engine and is very lightweight."
"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."
"The pricing scheme is very complex and difficult to understand."
"Data Factory could be improved in terms of data transformations by adding more metadata extractions."
"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."
"There's space for improvement in the development process of the data pipelines."
"I would like to see this time travel feature in Snowflake added to Azure Data Factory."
"Azure Data Factory can improve by having support in the drivers for change data capture."
"The Microsoft documentation is too complicated."
"If you have something like Cisco on top of it, you will have endless problems."
"It lacks a suite of tools suitable for fully processing data and moving it into decision support warehouses."
"It would be really good if Oracle considered enabling the tool to integrate with some other platforms that are deprecated simply for commercial reasons"
"Oracle Data Integrator (ODI) is already good as a solution. Still, it needs some editing of its preview package, or if the package is upgraded, that will make Oracle Data Integrator (ODI) even better."
"The tool should improve its pricing. It prevents the application of Oracle ODI on small and medium projects in countries like Croatia, Germany, or the US. While there are no technological obstacles to using it, the high price makes it unfeasible for projects with smaller budgets."
"The solution lacks some functions and features."
"In our company, we haven't tried consuming services from IoT in our company yet, and I would like to know if the solution will support IoT services in the next release."
"If there was an add-on tool to hide the performance issues and solve them for me, then I might be interested in that as it would provide me value."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Oracle Data Integrator (ODI) is ranked 4th in Data Integration with 67 reviews. Azure Data Factory is rated 8.0, while Oracle Data Integrator (ODI) is rated 8.2. 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 Data Integrator (ODI) writes "Straightforward to implement, scalable, and has good stability and documentation, but technical support could still be improved". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and SAP Data Services, whereas Oracle Data Integrator (ODI) is most compared with Oracle Integration Cloud Service, SSIS, Informatica PowerCenter, Oracle GoldenGate and Talend Open Studio. See our Azure Data Factory vs. Oracle Data Integrator (ODI) report.
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