Intel® Xeon® Processor E5 v4 Family Business Processing Benchmarks
Business Intelligence with Intel® Xeon® Processor E5-2600 v4 Product Family
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Business intelligence (BI) or decision support, contains two primary types of workloads: Data warehousing and data mart tools used to create and run data warehouses and data marts, and data analysis and data mining tools used to access data warehouses for online analytical processing (OLAP), data mining, data visualization, web query tools, and so on.
Business Intelligence Queries with TPC Benchmark* H
The TPC-H benchmark illustrates decision support systems that examine large volumes of data, execute queries with a high degree of complexity, and give answers to critical business questions.
The performance metric reported by TPC-H is called the TPC-H Composite Query-per-Hour Performance Metric (QphH@Size), and reflects multiple aspects of the capability of the system to process queries, including the selected database size against which the queries are executed, the query processing power when queries are submitted by a single stream, and the query throughput when queries are submitted by multiple concurrent users. See more at: http://www.tpc.org/tpch/
Big Data Analytics Systems with TPCx-BigBench (TPCx-BB)
The TPC Benchmark* Express-BigBench (TPCx-BB) measures the performance of end-to-end big data analytics by implementing 30 use cases that simulate big data processing, big data analytics, and reporting. The data represented are either structured, semi-structured, or un-structured data types. These use cases are frequently performed by big data operations at retailers with both physical and online store presence.
The TPCx-BB performance metric is called the Big Bench Query-per-minute (BBQpm@Size), where size is the scale factor of the data. The metric reflects three test phases: a load test that aggregates data from various sources and formats; a power test that runs each use case once to identify optimization areas and utilization patterns; and a throughput test that runs multiple jobs in parallel to test the efficiency of the cluster. TPCx-BB is implemented to work with modern big data analytics frameworks residing in the Hadoop ecosystem such as Map Reduce, Hive, Spark, Tez, and MLLIB. See more at: http://www.tpc.org/tpcx-bb/.