We performed a comparison between Oracle Data Integrator (ODI), SAP Data Hub, and WhereScape RED based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration."It allows us to use many languages to develop and to integrate practically all the technologies of the Oracle suite as well as those from non-Oracle vendors."
"I like that Oracle Data Integrator (ODI) has a straightforward setup and offers good technical support."
"The most valuable feature is Data movement."
"The installation of the client ODI Studio is easy."
"Integration with all systems is easy with Oracle Data Integrator, and it is easy to use. I have not used any other product, but with Oracle Data Integrator, we can easily connect to an ERP system, an SAP system, or a cloud application."
"ODI is a very accessible tool, especially since the mapping functionality has been added."
"The product has an ELT approach."
"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."
"SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database."
"The most valuable feature is the S/4HANA 1909 On-Premise"
"Its connection to on-premise products is the most valuable. We mostly use the on-premise connection, which is seamless. This is what we prefer in this solution over other solutions. We are using it the most for the orchestration where the data is coming from different categories. Its other features are very much similar to what they are giving us in open source. Their push-down approach is the most advantageous, where they push most of the processing on to the same data source. This means that they have a serverless kind of thing, and they don't process the data inside a product such as Data Hub. They process the data from where the data is coming out. If it is coming from HANA, to capture the data or process it for analytics, orchestration, or management, they go to the HANA database and give it out. They don't process it on Data Hub. This push-down approach increases the processing speed a little bit because the data is processed where it is sitting. That's the best part and an advantage. I have used another product where they used to capture the data first and then they used to process it and give it. In Data Hub, it is in reverse. They process it first and give it, and then they put their own manipulations. They lead in terms of business functions. No other solution has business functions already implemented to perform business analysis. They have a lot of prebuilt business functions for machine learning and orchestration, which we can use directly to get an analysis out from the existing data. Most of the data is sitting as enterprise data there. That's a major advantage that they have."
"Naturally produces a way to easily debug your DW data solutions."
"The most valuable feature is the metadata generated code."
"I like the data vault implementations."
"RED has provided us the ability to integrate, stage, and transform data from diverse sources into an enterprise-grade data warehouse which meets the needs of my organization, but it also enables us to easily and quickly make ETL or DW changes."
"WhereScape's deployment package is a fantastic feature. The application allows for selecting specific objects that you would like to deploy from one environment to another rather than deploying the entire database."
"Support is absolutely excellent, efficient, and timely."
"It has a built-in automatic scheduling environment."
"I found the initial setup very easy."
"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 interface of ODI could be improved. For example, navigating and finding functions can be difficult. For example, you have to know which step you need to go to look at where your job status is. The logical step is a bit complex compared to other tools. It's much easier to get a graphical view, but with ODI, it's graphical, plus you have to know all the other pieces that fit around it. You have to think about the logical and physical aspects."
"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."
"At present, when multiple steps are executed in parallel in the load plan and errors occur, the error handling mechanism does not function correctly."
"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."
"ODI could improve the ease of use. There is a steep learning curve to use the solution."
"It would be really good if Oracle considered enabling the tool to integrate with some other platforms that are deprecated simply for commercial reasons"
"The initial setup is complex, especially if you also have to install a console."
"The company has everything offshore."
"In 2018, connecting it to outside sources, such as IoT products or IoT-enabled big data Hadoop, was a little complex. It was not smooth at the beginning. It was unstable. It took a lot of time for the initial data load. Sometimes, the connection broke, and we had to restart the process, which was a major issue, but they might have improved it now. It is very smooth with SAP HANA on-premise system, SAP Cloud Platform, and SAP Analytics Cloud. It could be because these are their own products, and they know how to integrate them. With Hadoop, they might have used open-source technologies, and that's why it was breaking at that time. They are providing less embedded integration because they want us to use their other products. For example, they don't want to go and remove SAP Analytics Cloud and put everything in Data Hub. They want us to use SAP Analytics Cloud somewhere else and not inside the Data Hub. On the integration part, it lacks real-time analytics, and it is slow. They should embed the SAP Analytics Cloud inside Data Hub or support some kind of analysis. They do provide some analysis, but it is not extensive. They are moreover open source. So, we need a lot of developers or data scientists to go in and implement Python algorithms. It would be better if they can provide their own existing algorithms and give some connections and drop-down menus to go and just configure those. It will make things really quick by increasing the embedded integrations. It will also improve the process efficiency and processing power. Its performance needs improvement. It is a little slow. It is not the best in the market, and there are other products that are much better than this. In terms of technology and performance, it is a little slow as compared to Microsoft and other data orchestration products. I haven't used other products, but I have read about those products, their settings, and the milliseconds that they do. In Azure Purview, they say that they can copy, manage, or transform the data within milliseconds. They say that they can transform 100 gigabytes of data within three to five seconds, which is something SAP cannot do. It generally takes a lot of time to process that much amount of data. However, I have never tested out Azure."
"Nowadays there are some inconsistencies in data bases, however, they upgrade and release the versions to market."
"Customization could be better."
"Technical support isn't the best."
"No support for change data capture or delta detection - that must be custom coded ."
"Improve the object renaming ability (it works, but it could be more automated)."
"The scheduled jobs which are run by the WhereScape scheduler seem to be a strangely separate animal. Unlike all other WhereScape objects, jobs cannot be added to WhereScape projects. Also, unlike all other objects, jobs also cannot be deleted using a WhereScape deployment application."
"It could use a tool to diagnose what is missing from the environment for WhereScape to install successfully."
"They need a more robust support center. It has been a bit difficult to find solutions to problems that are out-of-the-box."
"Project-based searching of data objects in the data warehouse browser needs to be improved."
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