We performed a comparison between Apache Hadoop and SAP BW4HANA based on real PeerSpot user reviews.
Find out in this report how the two Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Data ingestion: It has rapid speed, if Apache Accumulo is used."
"It's good for storing historical data and handling analytics on a huge amount of data."
"High throughput and low latency. We start with data mashing on Hive and finally use this for KPI visualization."
"Hadoop File System is compatible with almost all the query engines."
"It is a file system for data collection. There are nodes in this cluster that contain all the information, directories, and other files. The nodes are based on the MySQL database."
"The most important feature is its ability to handle large volumes. Some of our customers have really large volumes, and it is capable of handling their data in terms of the core volume and daily incremental volume. So, its processing power and speed are most valuable."
"The performance is pretty good."
"The most valuable features are powerful tools for ingestion, as data is in multiple systems."
"The product has efficient performance."
"It is a stable solution...The initial setup was easy."
"SAP BW4HANA aids in managing data from ER to front-end analysis, contributes to ROI, and fosters business growth understanding. I like that the solution breaks down components to a very granular level, allowing for customization and implementation based on specific requirements. The solution is stable. The solution is scalable."
"You can do hierarchical alert slicing and dicing out-of-box, which is not available in other solutions. I haven't come across that in Oracle or any other software provider."
"The most valuable feature is that it's robust."
"The solution seamlessly integrates with SAP products."
"The most valuable features are the speed of reporting and the HANA database."
"The most valuable feature is that we can transform a huge amount of data and apply business logic as per the requirements."
"It would be helpful to have more information on how to best apply this solution to smaller organizations, with less data, and grow the data lake."
"The key shortcoming is its inability to handle queries when there is insufficient memory. This limitation can be bypassed by processing the data in chunks."
"The solution is very expensive."
"The stability of the solution needs improvement."
"I mentioned it definitely, and this is probably the only feature we can improve a little bit because the terminal and coding screen on Hadoop is a little outdated, and it looks like the old C++ bio screen. If the UI and UX can be improved slightly, I believe it will go a long way toward increasing adoption and effectiveness."
"Real-time data processing is weak. This solution is very difficult to run and implement."
"It would be good to have more advanced analytics tools."
"I would like to see more direct integration of visualization applications."
"I would like more integration."
"Connecting multiple sources is a challenge because you have to go through a lot of different setups."
"There's one area where the other vendors have an upper edge, which is the data lake. I think SAP is trying to figure out whether to stick with IQ, their own data lake solution, or push customers toward customer-preferred vendors, like Azure Data Lake, AWS, or any other provider."
"Challenges arise with real-time client requirements when clients are accustomed to Microsoft Excel's extensive features for data analysis. They expect similar flexibility and customization in the solution, particularly regarding headers displaying keys and descriptions or just keys. Achieving this level of customization can be challenging, and it's an area that may need improvement."
"The solution is not scalable. It does not have a data streaming feature as well."
"I don't see SAP actively supporting the solution now...a better support from SAP would be appreciated."
"From a technical perspective, it could be even more related to legacy systems. The connectivity requirement is quite high and requires systems that are up-to-date."
"We cannot integrate with third-party tools like Python or advanced integration options. You can't fine-tune tables within BW or generate specific views or reports."
Apache Hadoop is ranked 5th in Data Warehouse with 32 reviews while SAP BW4HANA is ranked 7th in Data Warehouse with 34 reviews. Apache Hadoop is rated 7.8, while SAP BW4HANA is rated 7.4. The top reviewer of Apache Hadoop writes "A file system for data collection that contains needed information and files". On the other hand, the top reviewer of SAP BW4HANA writes "An easy-to-operate and administer tool that needs to consider revising its existing licensing cost". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and IBM Netezza Performance Server, whereas SAP BW4HANA is most compared with Microsoft Azure Synapse Analytics, Snowflake, Amazon Redshift, SAP HANA and Microsoft Parallel Data Warehouse. See our Apache Hadoop vs. SAP BW4HANA report.
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We monitor all Data Warehouse 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.
