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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.
All performance measurements are accurate as of July 11 2017.
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.
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*.
The business warehouse edition for SAP HANA* measures….
This workload consists of three phases: a data load phase…, ; a query throughput phase…; and a query runtime phase…. The initial data volumes are multiples of 1.3 billion initial records.
SAP BW* Advanced Mixed Load (BW-AML) represents typical business warehouse customers looking for near real-time data analysis crucial to timely decision making. Phase 1 measures advanced query navigation steps per hour of large volumes of data. Phase 2 measures the runtimes of single queries and multi-level data load scenarios. Scale factors range from two billion (2B) to 16 billion records.
The STAC-M3* Benchmark is an industry standard benchmark that measures high-speed analytics on time series data, such as tick-by-tick market data (aka "tick database" stacks). This analytical approach is crucial to many trading functions, from algorithm development to risk management. Recent trends like the growth and sophistication of automated trading and the proliferation of new regulations place a premium on technology that can accelerate the analysis of time-series data. The specifications are agnostic to architecture, and the Shasta Suite allows pre-loading of the Kx Systems kdb+ database directly into memory.