Apache Hive vs. SAP BW/4HANA

Software work execution is on a large scale, it is good to use for new projects or organizational changes, data lineage mapping has always been dubious but this one has had good results. You can store and synchronize data from different departments, the storage process can be manual but it is best automated.

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Some scenarios where SAP BW/4HANA is well suited are retail industry, supply chain, finance, warehouse, stocking processes, BI, [and] some finance analytics reporting. Some scenarios where SAP BW/4HANA is less appropriate [is when] relational queries are needed [and] in some small business with infrastructure limitations. Another scenario that is less appropriate is for ABAP processes requirements.

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• Apache Hive allows use to write expressive solutions to complex problems thanks to its SQL-like syntax.
• Relatively easy to set up and start using.
• Very little ramp-up to start using the actual product, documentation is very thorough, there is an active community, and the code base is constantly being improved.

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• High speed data warehouse regardless of data volumes.
• Excellent integration with SAP systems and Data sets.
• Simplified data modelling due to columnar data base.

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• Some queries, particularly complex joins, are still quite slow and can take hours
• Previous jobs and queries are not stored sometimes
• Switching to Impala can sometimes be time-consuming (i.e. the system hangs, or is slow to respond).
• Sometimes, directories and tables don't load properly which causes confusion

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• Enterprise license pricing is very expensive and run-time license limits the usefulness of the tool.
• Integration with SAP Analytics cloud for write-back to BW/4HANA. Live connection is only read from SAC.
• Make run-time licenses more useful.

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Since I do not know the second data warehouse solution that integrate with HDFS as well as Hive.

Hive is a very good big data analysis and ad-hoc query platform, which supports scaling also. The BI processes can be easily integrated with Hadoop via the Hive. It can deal with a much larger data set that traditional RDBMS can not. It is a "must-have" component of the big data domain.

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SAP BW/4HANA requires specialized skillsets around data warehouse modeling and the access to data, however the modeling capabilities are intuitive and have now become accessible to both SAP and non-SAP data warehouse specialists. This new model allows for Interchangeable skillsets and access to a broader pool of experts throughout the industry, as well as easier access to data.

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Apache Hive is a FOSS project and its open source. We need not definitely comment on anything about the support of open source and its developer community. But, it has got tremendous developer support, awesome documentation. I would justify the fact that much support can be gathered from the community backup.

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SAP Max Attention and general support for SAP BW/4HANA is broadly available. Truth to be told, MaxAttention has a premium cost but brings great engineers. So this being an enterprise capability and extremely critical, we did not consider cost as the main factor since support works well. Just keep that in mind when making your selection.

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Besides Hive, I have used Google BigQuery, which is costly but have very high computation speed. Amazon Redshift is the another product, I used in my recent organisation. Both Redshift and BigQuery are managed solution whereas Hive needs to be managed

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SAP Analytics Cloud is complemented by SAP BW/4 HANA through connectors that work in real-time and allow the display of indicator information in interactive and user-friendly visualizations. SAP Data Services integrates with BW/4 HANA allowing to automate the loading of information in the system taking as a data source a wide variety of platforms.

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• Apache hive is secured and scalable solution that helps in increasing the overall organization productivity.
• Apache hive can handle and process large amount of data in a sufficient time manner.
• It simplifies writing SQL queries, hence helping the organization as most companies use SQL for all query jobs.

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• Faster turn-around to enhancements
• End users can query structures that are not limited to multi-dimensional models.
• Performance improvements means that business user can do more in the same time compared to traditional BW

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