Azure Data Factory vs SAP Data Hub comparison

"The most valuable feature of this solution would be ease of use."

"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."

"What I like best about Azure Data Factory is that it allows you to create pipelines, specifically ETL pipelines. I also like that Azure Data Factory has connectors and solves most of my company's problems."

"The function of the solution is great."

"The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable."

"Allows more data between on-premises and cloud solutions"

"The user interface is very good. It makes me feel very comfortable when I am using the tool."

"Its integrability with the rest of the activities on Azure is most valuable."

"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."

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

"If the user interface was more user friendly and there was better error feedback, it would be helpful."

"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."

"The user interface could use improvement. It's not a major issue but it's something that can be improved."

"It can improve from the perspective of active logging. It can provide active logging information."

"Some of the optimization techniques are not scalable."

"Data Factory has so many features that it can be a little difficult or confusing to find some settings and configurations. I'm sure there's a way to make it a little easier to navigate."

"I have not found any real shortcomings within the product."

"Snowflake connectivity was recently added and if the vendor provided some videos on how to create data then that would be helpful."

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

"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."

"The company has everything offshore."

"The solution's pricing is competitive."

"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."

"The licensing cost is included in the Synapse."

"The price you pay is determined by how much you use it."

"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."

"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."

"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."

"I don't see a cost; it appears to be included in general support."

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