We performed a comparison between Informatica PowerCenter and SAP Data Hub based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration."Easy, scalable, robust platform to integrate heterogeneous source platform's data into the unified data warehouse."
"Complex transformations can be easily achieved by using PowerCenter. The processing layer does transformations and other things. About 80% of my transformations can be achieved by using the middle layer. For the remaining 15% to 20% transformations, I can go in and create stored procedures in the respective databases. Mapplets is the feature through which we can reuse transformations across pipelines. Transformations and caching are the key features that we have been using frequently. Informatica PowerCenter is one of the best solutions or products in the data integration space. We have extensively used PowerCenter for integration purposes. We usually look at the best bridge solution in our architecture so that it can sustain for maybe a couple of years. Usually, we go with the solution that fits best and has proven and time-tested technology."
"The ability to scale through partitions helped us to improve the performance."
"Informatica PowerCenter has been implementing mapping design, data flow, and workflow execution for years."
"The reliability of the product and the way of orchestration of different services is valuable to us."
"The features I find most valuable is that the solution is very user-friendly and the graphical design is very easy to understand."
"Reusable definition of data sources and the out-of-the-box availability of a large number maplets for common transformation functions."
"I like the completeness of the way I can build ETL workflows."
"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."
"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"
"I would like to see it be able to import data from NoSQL."
"There can be scalability issues. Huge amounts of data ingestion will impact performance."
"PowerCenter could be improved by having more big data components. Normally, we prefer Informatica as a relational database, but nowadays, companies are trying to understand and use big data components. I think it would be useful if we had more chances to create a hub ecosystem because customers try to use some data integration tasks by SQL, Spark and Spark codes, and Scala, but at the end of the day, the company will understand that we need to trace all the steps. An ETL tool is a must for that company, if we're talking about the regulated industries like finance, telcos, etc. If Informatica's biggest ecosystems feature were okay, I would prefer to use it."
"The only problem with this product is the level of complexity with the number of levels of transformation that you have to go through."
"Some of the conversions are done inside the product. We use work tables that are created by the engine itself, but the names of the work tables are very long, and they don't have any meaning, which makes it a bit difficult to understand and follow exactly what is happening inside."
"This solution needs the functionality to do batch processing of data. It also lacks connectivity to NoSQL, unstructured data sources."
"I found it is kind of weird that not all of the mapping changes are treated as true changes."
"What I didn't like about it is that the platform itself is not great at distributed processing. When you need high parallel processing, it has some inherent issues. We had to use Java transformation, and it did not go very well. I have heard that it is going to the cloud, but we haven't tried that."
"The company has everything offshore."
"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."
Informatica PowerCenter is ranked 3rd in Data Integration with 78 reviews while SAP Data Hub is ranked 26th in Data Governance with 3 reviews. Informatica PowerCenter is rated 8.0, while SAP Data Hub is rated 7.6. The top reviewer of Informatica PowerCenter writes "Stable, provides good support, and integrating it with other systems is very fast, but its pricing is expensive". On the other hand, the top reviewer of SAP Data Hub writes "The solution is seamless, but the database sometimes leads to confusion". Informatica PowerCenter is most compared with Informatica Cloud Data Integration, Azure Data Factory, SSIS, Databricks and AWS Glue, whereas SAP Data Hub is most compared with Microsoft Purview Data Governance, SAP Data Services, Alation Data Catalog, Collibra Governance and Azure Data Factory.
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