We performed a comparison between SAP Data Hub and SSIS based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Collibra, Informatica and others in Data Governance."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"
"The technical support is very good."
"The most valuable thing is that it is easy to connect with Microsoft tools. In Europe, particularly in France, a lot of companies use Excel, SQL Server, and other Microsoft tools, and it is easier to connect SSIS with Microsoft tools than other products."
"It's something I needed for bulk imports. I'm not a big fan of it, but I haven't seen anything better."
"This solution is easy to implement, has a wide variety of connectors, has support for Visual Basic, and supports the C language."
"Data Flows are the main component we use. These can range from a simple source to sink ETL, to many source to many sink dataflows."
"It is easy to set up the solution."
"The most important features are it works well and provides self-service BI."
"The initial setup was easy."
"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."
"Nowadays there are some inconsistencies in data bases, however, they upgrade and release the versions to market."
"Future releases should improve the data lineage, as it currently is not good."
"A change in the metadata source cripples the whole ETL process, requiring each module to be manually reopened."
"We're in the process of switching to Informatica, and we need to work out data lineage and data profiling and to improve the quality of our data. SSIS, however, is not that compatible with Informatica. We managed to connect it to Informatica Metadata Manager, but we don't get good lineage, so we have to redo all our ETLs using the Informatica process in order to accept the proper data lineage."
"We have issues with SSIS connectors while extracting data from Excel sources."
"There are a lot of things that Microsoft could improve in relation to SSIS. One major problem we faced was when attempting to move some Excel files to our SQL Server. The Excel provider has a limitation that prevents importing more than 255 columns from a particular Excel file to the database. This restriction posed a significant issue for us."
"SSIS is cumbersome despite its drag-and-drop functionality. For example, let's say I have 50 tables with 30 columns. You need to set a data type for each column and table. That's around 1,500 objects. It gets unwieldy adding validation for every column. Previously, SSIS automatically detected the data type, but I think they removed this feature. It would automatically detect if it's an integer, primary key, or foreign key column. You had fewer problems building the model."
"We In upgrading SSIS, we encountered challenges fixing SQL Server and performance issues, including problems during a failover in our data warehouse."
"SSIS doesn't have a very good user interface, but if you can work with it, it'll provide you with almost all of the functionality."
SAP Data Hub is ranked 26th in Data Governance with 3 reviews while SSIS is ranked 2nd in Data Integration with 69 reviews. SAP Data Hub is rated 7.6, while SSIS is rated 7.6. The top reviewer of SAP Data Hub writes "The solution is seamless, but the database sometimes leads to confusion". On the other hand, the top reviewer of SSIS writes "Maintaining the solution and contacting its support team is easy". SAP Data Hub is most compared with Microsoft Purview Data Governance, SAP Data Services, Alation Data Catalog, Collibra Governance and Qlik Replicate, whereas SSIS is most compared with Informatica PowerCenter, Talend Open Studio, IBM InfoSphere DataStage, Oracle Data Integrator (ODI) and AWS Glue.
We monitor all Data Governance reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
