TPCxBBs

TPCxBBs refers to the family of benchmark specifications developed by the Transaction Processing Performance Council (TPC) for evaluating big data analytics platforms. The core benchmark, often called TPCxBB, is designed to assess how well a system ingests, stores, and analyzes large-scale data using a realistic mix of analytics tasks. The “s” in TPCxBBs is sometimes used to denote multiple published results or variants of the benchmark run from different vendors or configurations.

The benchmark centers on the BigBench workload, a collection of analytical queries and data maintenance tasks that simulate common business analytics scenarios. A synthetic data generator creates datasets of configurable size (scale factor) and distribution, enabling reproducible testing across platforms. The benchmark defines a run protocol, validation rules, and performance requirements to ensure that results are comparable between different hardware, software stacks, and configurations.

Metrics commonly associated with TPCxBB include a throughput measure, typically reported as queries per hour on the Big Data workload (QphBB). In addition, results may include supplementary metrics such as latency for individual queries, resource utilization, and a price-performance calculation where applicable. The specification requires detailed disclosure of the tested hardware, software versions, cluster topology, and runtime parameters to enable replication.

TPCxBBs are used by vendors, researchers, and enterprises to compare the performance and scalability of big data platforms—ranging from Hadoop and Spark-based systems to newer analytics engines—under standardized conditions. They aim to provide objective, repeatable assessments while reflecting practical big data workloads.