TPC-DS is the de-facto industry standard benchmark for measuring the performance of decision support solutions including, but not limited to,
Big Data systems.
This benchmark illustrates decision support systems that:
The current version is v2. It models several generally applicable aspects of a decision support system, including queries and data maintenance.
Although the underlying business model of TPC-DS is a retail product supplier, the database schema, data population, queries, data maintenance model and
implementation rules have been designed to be broadly representative of modern decision support systems.
- Examine large volumes of data
- Give answers to real-world business questions
- Execute SQL queries of various operational requirements and complexities (e.g., ad-hoc, reporting, iterative OLAP, data mining)
- Are characterized by high CPU and IO load
- Are periodically synchronized with source OLTP databases through database maintenance functions
- Run on “Big Data” solutions, such as RDBMS as well as Hadoop/Spark based systems
TPC-DS Version 2 enables emerging technologies, such as Big Data systems, to execute the benchmark.
The major changes in Version 2 are in the area of ACID (Atomicity, Consistency, Isolation and Durability), data maintenance,
metric calculation and execution rules.
Major changes in Version 2 are described in its companion document.