IBM InfoSphere Information Server vs SAP Data Hub comparison

"This solution has reduced the time it takes for ETL. We took an existing Teradata ETL application from three days to eight minutes."

"Stability-wise, I rate the solution a ten out of ten."

"Over the years of working with IBM InfoSphere Information Server, I see basically the strength of the tool, capability, and load balancing, which I see is really good."

"The integration with different technologies is the most valuable feature."

"The initial IBM InfoSphere Information Server is straightforward and you can choose what type of installation you want, such as a customized installation, with clear-cut documentation that, if followed, works fine and the installation has not given us issues."

"Deploying the solution is straightforward for me."

"Reduces the loading and development time for Datawarehouse ETL."

"Data connections, data partitioning, flexibility, and performance are the most valuable features."

"They lead in terms of business functions, and no other solution has business functions already implemented to perform business analysis, with a lot of prebuilt business functions for machine learning and orchestration that we can use directly to get an analysis out from the existing enterprise data."

"Having this solution enables us to approach our clients to upgrade their databases, and we upgrade them according to their business requirements."

"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."

"IBM InfoSphere Information Server should be more scalable. It should have the option to change the configuration to run on a single, non-multiple node, or multi-threading processing."

"There are certain shortcomings in the cloud side of the solution, where improvements are required."

"This solution would benefit from the engine being made more lightweight."

"Heavy use of scratch disk which sometimes leads to failure."

"IBM InfoSphere Information Server should be more scalable. It should have the option to change the configuration to run on a single, non-multiple node, or multi-threading processing."

"Customer Service: It's poor."

"Their technical support needs improvement."

"We have decided to decrease the usage of metadata management because we did not see any significant advantages."

"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."

"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."

"The company has everything offshore."

"Nowadays there are some inconsistencies in data bases, however, they upgrade and release the versions to market."

"The licensing cost of IBM InfoSphere Information Server depends on how many users there are."

"The Cloud is very expensive, but SAP HANA previous service is okay."