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."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's best features are customization, integration with other versioning tools, and the ability to define new knowledge modules."
"It has the ability to easily load slowly changing dimensions."
"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."
"The tool improved our data integration workflow primarily due to its compatibility with Oracle. Its integration makes it very convenient for analytics. Its most valuable feature is robust extended capability. The solution's debugging capabilities are good."
"The CAEM is very useful in its modularity and portability."
"It's completely user-friendly."
"It can integrate with more recent databases like Cassandra, Hadoop, and other more recent Big Data databases."
"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."
"SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database."
"Naturally produces a way to easily debug your DW data solutions."
"Quickly develops a data warehouse for our organization with documentation and can track back/forward features."
"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 is really helpful in terms of architecture data. Everything is one of automation. Two people can do thousands of tables in one day or two. It saves a lot of time."
"The tool supports multiple target update methods."
"Their support staff are very knowledgeable, courteous, and professional. I feel their support staff go above and beyond to assure their customers are satisfied."
"Data transformations and rollups are easy to accomplish."
"I like the data vault implementations."
"It has been very good. Just recently, I've faced an issue, but I solved it somehow. While integrating with a file, I faced an issue where I wanted output files, and I had used the text field limited quotations, but at the end of the file, there was a line breakage for the last column. So, we just removed the text field because it was not working correctly for us."
"Reverse engineering is complicated and challenging to manage."
"I would only point out some minor bugs or glitches in the development interface (ODI studio)."
"ODI could improve by focusing on streamlining its features without unnecessary overhead."
"I rate it a seven out of 10 because there is room for growth because ODI is still new, in comparison to Informatica, which is a mature product."
"The resource management aspect of the solution could be improved."
"The price needs to be lowered. It's too expensive."
"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 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."
"No support for change data capture or delta detection - that must be custom coded ."
"Customization could be better."
"It could use a tool to diagnose what is missing from the environment for WhereScape to install successfully."
"Project-based searching of data objects in the data warehouse browser needs to be improved."
"The solution can be a little more user-friendly on enterprise-level where people use it."
"Improve the object renaming ability (it works, but it could be more automated)."
"They need a more robust support center. It has been a bit difficult to find solutions to problems that are out-of-the-box."
"Jobs cannot be deleted via the deployment package. When deploying from dev to QA or production, a job has to be retired. The job has to be manually removed from the target environment."
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