DeepBench-Benchmarking JSON Document Stores

Abstract

The growing popularity of JSON as exchange and storage format in business and analytical applications led to its rapid dissemination, thus making a timely storage and processing of JSON documents crucial for organizations. Consequently, specialized JSON document stores are ubiquitously used for diverse domain-specific workloads, while a JSON-specific benchmark is missing. In this work, we specify DeepBench, an extensible, scalable benchmark that addresses nested JSON data, as well as queries over JSON documents. DeepBench features configurable domain-independent (e. g., varying document sizes, concurrent users) and JSON-specific scale levels (e. g., object, array nesting). The evaluation of well-known document stores with a prototypical DeepBench implementation shows its versatility and gives new insights into potential weaknesses that were not found by existing, non-JSON benchmarks