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Difference between SAP HANA and Hadoop

Updated Jan 14, 2020

SAP HANA vs. Hadoop

SAP HANA is referred to as the in-memory technology, whereas Hadoop from Cloudera is known as a big data solution. SAP HANA is used for a higher-level and operational analysis, whereas Hadoop is used as a tool for pre-processing and aggregation of very detailed data. In HANA, the unit of data size is costly, and the speed at which data analysis is done is usually swift data analysis. In Hadoop, the size of the unit of data size is quite small.

Listed below are some of the significant differences between SAP HANA and Hadoop. However, both HANA and Hadoop are equally competitive, useful, and offer the best to their customers. Yet, there are a few pointers on which either of them is superior to others. Let us examine these features:

Topic SAP HANA Hadoop
Introduction SAP HANA is referred to as the in-memory technology. SAP HANA is more known as a platform that comes with inherent capabilities that allow much faster and efficient processing from the standpoint of Big data, and data is more real-time and can be utilized for data analytics. Read more here about SAP HANA Hadoop from Cloudera's is known as a big data solution. This provides the base Hadoop is well suited for data that is stored and unstructured. It is suitable for working on huge files and is tolerant to hardware and software failures. Read more here about HADOOP
Databases being offered SAP offers several database products which cross each other in both characteristics and usage area. Vast amounts of data can be stored in Hadoop. This is ideally suited for storing data, which is unstructured, and huge files can be manipulated and is also known to be very tolerant of both hardware and software failures.
Data size In SAP HANA, the unit of data size is costly, and the speed at which data analysis is done is usually swift data analysis. With this kind of set up, the option of not extracting data to another storage for analysis is done as that’s usually done with traditional OLTP databases, which remove the expenses of integration with and support of yet another data mart. In Hadoop, the size of the unit of data size is quite small. This leads to exploring the door of analyzing massive input data arrays, which were earlier ignored all because of the enormous data size. The speed of data analysis is quite low. There is a lot of scope for improvement, which primarily requires adding more RAM to cluster, thus making the solution considerably more expensive.
Hadoop for mainly destined for data analysis and transformation (ETL)
Usage SAP HANA for a higher-level and operational analysis. Hadoop is used as a tool for pre-processing and aggregation of very detailed data.
Features SAP HANA is more simplified, provides coverage end to end data processing, and is optimized- used in the field of application processing Hadoop scales it out for unlimited raw data and is used in commodity hardware, doesn’t require anything special.
Costs SAP HANA is very costly. Hadoop, on the other free, is free of cost. All you need to do is download the free versions and install these. It can be strung together on any random hardware.
Companies Bluefin Solutions Ltd, SAP SE, Virtustream, Inc., SuccessFactors, INC, companies using SAP HANA. Lithium Technologies, LinkedIn, Facebook, Sprint, Oracle are some companies using Hadoop.


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