Apache Hive vs. SAP BW/4HANA

Apache Hive shines for ad-hoc analysis and plugging into BI tools. Its SQL-like syntax allows for ease of use not for only for engineers but also for data analysts. Through our experience, there are probably more desirable tools to use if you are planning on integrating Hive into your processing pipeline.

Incentivized

SAP BW/4HANA is well suited for warehousing solution when majority of the source systems are SAP. With ODP BW and ODP CDS view source system types, SAP standard extractors and CDS view based extractors provides the best support for delta extraction with less lead time for data availability to report. It is less appropriate for the scenarios to do AI/ML use cases for forecasting and predictive scenarios as there are limited options. It is less appropriate for the scenarios to use recent responsive AI tools and LLM.

Incentivized

• Hive syntax is almost like SQL, so for someone already familiar with SQL it takes almost no effort to pick up Hive.
• To be able to run map reduce jobs using json parsing and generate dynamic partitions in parquet file format.
• Simplifies your experience with Hadoop especially for non-technical/coding partners.

Incentivized

• BI and Reporting out of the ERP Layer
• Self Service Capabilities to build reports and cubes out of SAP
• Great Performance for simple and analytical reporting out of SAP
• Broad availability of BW Tools to integrate - such as Business Explorer

Incentivized

• Use Hive for analytical work loads. Write once and read many scenarios. Do not prefer updates and deletes.
• Behind scenes Hive creates map reduce jobs. Hive performance is slow compared to Apache Spark.
• Map reduce writes the intermediate outputs to dial whereas Spark operates in in-memory and uses DAG.

Incentivized

• It would be nice to see tools available within SAP BW/4HANA for cross platform esp. other SAP systems integration from a data extraction and scheduling standpoint. This is to ensure BW data stays consistent with its sources and is refreshed only after completion of core business process activities in its source systems. This is also relevant from a SAC and Datasphere integration standpoint for data being fed from SAP BW/4HANA as these platforms currently only support time based scheduling options with no dependencies possible against SAP BW/4HANA processes. Currently most companies employ an external third party scheduling tool to manage this.
• With the advent of Analysis for Office the ability to publish AFO workbooks has been lost directly from the SAP BW/4HANA platform unlike its BEx Analyzer predecessor which had the Broadcaster. The use of BO Platform is not an ideal use case for this functionality which is very basic in its scope.
• In this age of AI would be nice to see functionality introduced for AI co-pilots like Joule to speed by data modeling and scheduling activities as well as a natural language based querying options within AFO.

Incentivized

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.

Incentivized

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.

Incentivized

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.

Incentivized

I never experienced any support issue when using SAP BW/4HANA. The only issues I faced were at the moment of installing the tool in my computer but I got support from the local IT department of my company and was quickly fixed

Incentivized

We have used a simple but necessary function such as merging certain data tables, which although they may be from different areas, complement each other or are necessary, you can use metadata if what you need is to validate the origin of your information and what impact it has, is also feasible.

Incentivized

We chose SAP BW/4HANA for its out of the box integration and ETL capabilities with our landscape of other SAP solutions in addition to the pre-build SAP delivered business content. Integrated BPC also made it a perfect choice for planning and consolidation in one integrated environment. Qlik and Power BI were primarily used as additional visualization tools for business users with data integration against SAP BW/4HANA as opposed to being used as a full blown data warehousing platform. This was however before the introduction of SAP Analytics Cloud.

Incentivized

• Good ROI for being able to access data easily across the network, we have large amounts of data and this is a good system to access it
• Good ROI for being easy to learn how to use for new employees, not much time spent which saves costs
• Good ROI for being able to integrate with Spark and other applications, hence data can be analyzed through programs

Incentivized

• Still acting as important point of source for major decisions
• After BW/4HANA Migration there is 20 % increase in the extractions to BW system
• Still we are yet to find a better investment for reporting in SAP , though we use SAC, which has its own issues while dealing with huge volumes of data

Incentivized