Apache Hive vs. SAP Business Warehouse

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 is best for: 1. Large enterprises 2. Enterprises with 3+ legacy systems with entrenched users (politically difficult to merge) 3. Enterprises with employees who can understand both the technical capabilities of SAP BW and the needs of the business users - ability to speak both languages, otherwise the program could be unwieldy and potentially underutilized (it's not particularly inexpensive) SAP BW is less appropriate for: 1. Small enterprises 2. Enterprises who have well established, same location, CRM and UFS - the integration of data analysis will be easier and less expensive with other solutions 3. HANA

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

• ETL, great at taking data from OLTP source, flat file, etc... Easy drag and drop for transformations.
• Great reporting possibilities, easy to connect with BO, BPC, etc...
• Great Master Data Management (MDM )for BPC - helps us maintain master data for BPC.

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

• Age of software is showing as it struggles with very large data modules, which were not as prevalent in its early years
• Querying performance at times can be very slow
• Support and development for BEx has been discontinued or hard to find.

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

It needs minimal trainings and can perform tasks of data management and reporting.

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

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

SAP Business Warehouse scores higher in data warehouse functionalities for integration to SAP ERP and other SAP solutions such as SAP CRM, SAP APO, and SAP SRM. Standard SAP data source extractors which are available in SAP ERP can be used immediately for full or delta replication into SAP Business Warehouse. System governance in SAP Business Warehouse is top-notch with change management support for migration between system landscape from the development system to production system.

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

• It has helped cut down on parts shortages with the minimum stock flags.
• People are able to track down parts easier because they can see where they were last used.
• Our sales team has better visibility on lead times so they can accurately quote our customers.

Incentivized