Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
149 tokens/sec
GPT-4o
9 tokens/sec
Gemini 2.5 Pro Pro
47 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Benchmarking JSON BinPack (2211.12799v1)

Published 23 Nov 2022 in cs.SE

Abstract: In this paper, we present benchmark results for a pre-production implementation of a novel serialization specification: JSON BinPack. JSON BinPack is a schema-driven and schema-less sequential binary serialization specification based on JSON Schema. It is rich in diverse encodings, and is developed to improve network performance and reduce the operational costs of Internet-based software systems. We present benchmark results for 27 JSON documents and for each plot, we show the schema-driven and schema-less serialization specifications that produce the smallest bit-strings. Through extensive plots and statistical comparisons, we show that JSON BinPack in schema-driven mode is as space-efficient or more space-efficient than every other serialization specification for the 27 documents under consideration. In comparison to JSON, JSON BinPack in schema-driven mode provides a median and average size reductions of 86.7% and 78.7%, respectively. We also show that the schema-less mode of the JSON BinPack binary serialization specification is as space-efficient or more space-efficient than every other schema-less serialization specification for the 27 documents under consideration. In comparison to JSON, JSON BinPack in schema-less mode provides a median and average size reductions of 30.6% and 30.5%, respectively. Unlike other considered schema-driven binary serialization specifications, JSON BinPack in schema-driven mode is space-efficient in comparison to best-case compressed JSON in terms of the median and average with size reductions of 76.1% and 66.8%, respectively. We have made our benchmark results available at jviotti/binary-json-size-benchmark on GitHub.

Citations (1)

Summary

We haven't generated a summary for this paper yet.