Qlik Replicate vs SAP Data Hub comparison

"From a technical perspective, this is an excellent product."

"It's very user-friendly when it comes to settings and configuration. It also offers very detailed logging about warnings and errors."

"A valuable feature of Qlik Replicate is that you do not need ETL; it's easy to use—you choose two systems and it automatically replicates them."

"Its capability to replicate the data without impacting the source databases performance-wise is the most useful aspect."

"From a technical perspective, this is an excellent product."

"It implements new real-time capabilities for data ingestion, works in hybrid mode that is a hybrid cloud, is very good, and it looks like it has very good performance, so we're quite happy."

"My advice to others looking into implementing Qlik Sense is that it's a great product."

"It enables us to transform data at the latest stage rather than in ETL loads, so it's more ELT which is one of the advantages. It is also in near real-time, which brings significant advantage for our embedded analytics approach."

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

"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."

"The most valuable feature is the S/4HANA 1909 On-Premise"

"SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database."

"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."

"We would like to see more details in messages about errors with the system."

"When you remote into it the Qlik Replicate UI a lot of times it just freezes. We set up the EC2, to allow them to go to the server and click on the Replicate icon, it just opens up and just sits there. At that point, we have to go into the EC2 and then reboot the server. This should be fixed, it is frustrating."

"The UI and data version control can be improved."

"It would be better if the solution’s pricing were more obvious."

"Support-wise, this solution is in need of improvement."

"This product could be improved by providing more insight regarding errors. We tried to debug it, but we could not trace the error message."

"We'd like better connectivity."

"Support-wise, this solution is in need of improvement."

"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."

"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."

"Qlik Replicate is mainly suited for large companies. However, it is too costly for small businesses. Its pricing is high."

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate Qlik Replicate's pricing a nine out of ten."

"Pricing for this solution is very reasonable."

"Qlik Replicate is not expensive, compared to GoldenGate."

"Unlike Azure, where you pay based on consumption, Qlik Replicate seems to charge per endpoint."

"Overall, Qlik is an expensive solution. You need to pay for all additional features that you would like to use."

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