Anonymous UserSenior Manager at a tech services company
Viplove KhushalaniInnovation Lead at a tech services company
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"The solution has a good interface and the integration with GitHub is very useful."
"The user interface is very good. It makes me feel very comfortable when I am using the tool."
"From what we have seen so far, the solution seems very stable."
"Data Factory itself is great. It's pretty straightforward. You can easily add sources, join and lookup information, etc. The ease of use is pretty good."
"The most valuable features are data transformations."
"Powerful but easy-to-use and intuitive."
"It is a complete ETL Solution."
"From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connects and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature."
"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."
"In the next release, it's important that some sort of scheduler for running tasks is added."
"The solution should offer better integration with Azure machine learning. We should be able to embed the cognitive services from Microsoft, for example as a web API. It should allow us to embed Azure machine learning in a more user-friendly way."
"The solution needs to integrate more with other providers and should have a closer integration with Oracle BI."
"On the UI side, they could make it a little more intuitive in terms of how to add the radius components. Somebody who has been working with tools like Informatica or DataStage gets very used to how the UI looks and feels."
"The speed and performance need to be improved."
"The product could provide more ways to import and export data."
"The Microsoft documentation is too complicated."
"The user interface could use improvement. It's not a major issue but it's something that can be improved."
"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."
"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"This is a cost-effective solution."
"The price you pay is determined by how much you use it."
"Understanding the pricing model for Data Factory is quite complex."
"I would not say that this product is overly expensive."
Create, schedule, and manage your data integration at scale with Azure Data Factory - a hybrid data integration (ETL) service. Work with data wherever it lives, in the cloud or on-premises, with enterprise-grade security.
The SAP® Data Hub solution enables sophisticated data operations management. It gives you the capability and flexibility to connect enterprise data and Big Data and gain a deep understanding of data and information processes across sources and systems throughout the distributed landscape. The unified solution provides visibility and control into data opportunities, integrating cloud and on-premise information and driving data agility and business value. Distributed processing power enables greater speed and efficiency.
Azure Data Factory is ranked 3rd in Data Integration Tools with 20 reviews while SAP Data Hub is ranked 5th in Data Governance with 1 review. Azure Data Factory is rated 7.8, while SAP Data Hub is rated 6.0. The top reviewer of Azure Data Factory writes "Reasonably priced, scales well, good performance". On the other hand, the top reviewer of SAP Data Hub writes "Good push-down approach, on-premise connection, and integration with SAP products, but needs better performance and integration with other solutions". Azure Data Factory is most compared with Informatica PowerCenter, Talend Open Studio, Informatica Cloud Data Integration, SAP Data Services and IBM InfoSphere DataStage, whereas SAP Data Hub is most compared with SAP Data Services, Palantir Foundry, SAP Process Orchestration, Denodo and Talend Data Fabric.
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