KABEYA TSHISEBA Cedric1, DIONGA NDIBU Ornella2, LUBONGO MUEMBE Georgine3, Gloire Alonda Madomba4, Simplice EALE BOTULI5, Mangoma Joel Joel6, and Kevin Mongoy Bonyolo7
1 Département de Mathématique et Informatique, Faculté de Sciences, Université Pédagogique Nationale (UPN), Ngaliema, Kinshasa, RD Congo
2 Département de Mathématique et Informatique, Faculté de Sciences, Université Pédagogique Nationale (UPN), Ngaliema, Kinshasa, RD Congo
3 Département de Mathématique et Informatique, Faculté de Sciences, Université Pédagogique Nationale (UPN), Ngaliema, Kinshasa, RD Congo
4 Mbandaka University, RD Congo
5 Département de Mathématique et Informatique, Faculté de Sciences, Université Pédagogique Nationale (UPN), Ngaliema, Kinshasa, RD Congo
6 Pedagogic National University, RD Congo
7 Pedagogic National University, RD Congo
Original language: English
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Abstract
JSON (JavaScript Object Notation) and XML (Extensible Markup Language) represent two fundamental approaches to data structuring, each optimized for distinct computational paradigms. This study provides a systematic comparative analysis based on four key parameters: syntactic structure, performance metrics (file size and parsing speed), validation capabilities, and ecosystem adoption. Quantitative measurements demonstrate that JSON generates files 30-50% smaller than XML and achieves parsing speeds 2-10 times faster, making it optimal for REST APIs, mobile applications, and microservices where performance is critical. Conversely, XML’s sophisticated validation through XSD schemas, namespace support, and transformation capabilities via XSLT render it indispensable for regulated sectors requiring semantic rigor—including legal documents, standardized B2B exchanges, and long-term digital archives. The analysis reveals that these formats are not competitors but complementary tools: JSON embodies pragmatic efficiency for application-oriented exchanges, while XML provides structural integrity for complex document ecosystems. Recent evolutionary developments—including JSON Schema (RFC 8927) and JSON-LD for semantic annotations, alongside XML simplifications—demonstrate contextual adaptation rather than convergence. The findings establish that optimal format selection depends on project-specific constraints: data complexity requirements, validation needs, performance thresholds, and target ecosystem integration. This study contributes a structured decision-making framework enabling architects to select appropriate formats based on empirical criteria rather than ideological preferences.
Author Keywords: JSON, XML, Data Interchange Formats, Comparative Analysis, Web APIs, Document Engineering, Performance Evaluation, Data Serialization.
