Azure Data Factory vs SAP Data Hub comparison

"I like that it's a monolithic data platform. This is why we propose these solutions."

"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."

"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."

"From what we have seen so far, the solution seems very stable."

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

"We haven't had any issues connecting it to other products."

"We have been using drivers to connect to various data sets and consume data."

"The most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."

"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."

"Some known bugs and issues with Azure Data Factory could be rectified."

"Real-time replication is required, and this is not a simple task."

"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."

"I have encountered a problem with the integration with third-party solutions, particularly with SAP."

"Azure Data Factory can improve the transformation features. You have to do a lot of transformation activities. This is something that is just not fully covered. Additionally, the integration could improve for other tools, such as Azure Data Catalog."

"The pricing model should be more transparent and available online."

"There aren't many third-party extensions or plugins available in the solution."

"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."

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

"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."

"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."

"Azure products generally offer competitive pricing, suitable for diverse budget considerations."

"Data Factory is affordable."

"Azure Data Factory gives better value for the price than other solutions such as Informatica."

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

"The licensing cost is included in the Synapse."

"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."

"Understanding the pricing model for Data Factory is quite complex."

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